Gender Survey: CARE Haiti Health Sector, Life-Saving Interventions for Women and Girls in Léogâne and Carrefour
Summary — A gender survey conducted in Léogâne and Carrefour for CARE's health programming.
Key Findings
- Primary data collection at commune level in Léogâne and Carrefour.
- Documents its training, pretests and ethical review, which survey reports often omit.
- 120 pages, August 2013.
Full Description
A gender survey conducted in Léogâne and Carrefour for CARE's health programming. It is commune-level primary data collection on women's and girls' access to health services, at a scale most gender analysis in Haiti does not reach.
Full Document Text
Extracted text from the original document for search indexing.
Report
Gender Survey
CARE HAITI
HEALTH SECTOR
Life Saving Interventions for Women and Girl in Haiti
Conducted in Communes of
Leogane and Carrefour,
Haiti
22nd August 2013
Submitted by Timothy T Schwartz
Survey Teams Getting Ready to go to Work in Carrefour
Acknowledgements
This report was enriched by guidance from CARE staff Geneviève Blaise, Lindsay Carter, and
Gladys Mayard, as well as CARE consultant Beverly Stauffer. Any opinions or construed bias
are to be attributed to the author. The questionnaire was refined, the work supervised and the
actual surveys conducted by a team of 2 consultant-supervisors, 14 consultant-enumerators and a
data monitor and accountant.
Data monitor and accountant
• Stephanie Pierre
Consultant-supervisors
• Emile Pharrel
• Guy Pavilus
Consultant-enumerators
• Previlon Renaud
• Intervol Jude
• Janvier Judithe
• Lacombe Dieula
• Vilfort Judith
• Joseph Ricardo
• Simon Joana
• Fils Sonia
• Ambeau Egain
• Prophete Sylvestre
• Sylvain Marcos
• Emile Marckenson
• Vilfort Sabine
• Remy Odile
ACRONYMS
CARE Cooperative Agreement for Relief Everywhere
DHS Demographic & Health Surveys
Enquête Mortalité, Morbidité, Utilisation des
EMMUS Services [Mortality, Morbidity, Use of
Services].
FP Family Planning
GBV Gender Based Violence
MSF Médecins Sans Frontières
NGO Non Governmental Organization
United States Agency to International
USAID
Development
Contents
Summary of Important Findings ..................................................................................................... 1
1. Overview ................................................................................................................................. 2
2. Review of the Literature ......................................................................................................... 4
3. Questionnaire ........................................................................................................................ 10
Training and pretests ................................................................................................................. 11
Ethical Review .......................................................................................................................... 11
4. Methodology ......................................................................................................................... 12
Clusters, Selection, and number of respondents ....................................................................... 12
Respondents per Residence, Absenteeism and Replacement ................................................... 13
Date and duration of survey ...................................................................................................... 13
Team Structure and logistics ..................................................................................................... 13
Interviews and data monitoring ................................................................................................ 13
Equipment and software ........................................................................................................... 14
Sample Stratification ................................................................................................................. 14
5. Respondent Profiles: Origin, Urban vs Rural, Work and Education ................................... 15
6. The Household ...................................................................................................................... 19
Defining Household Heads ....................................................................................................... 19
Urban vs. Rural Household Dimension ................................................................................ 20
Household Headship and Material Status Indicators ................................................................ 21
Headship and Economic Contributions .................................................................................... 24
Differential Impact of Women vs. Men Being in Control of Household Resources ................ 27
Household Expenditures on Food ......................................................................................... 27
Male vs. Female Control Over the Household Budget ......................................................... 29
Female Control of the Budget and Household Expenditures on Food ................................. 30
Chores ....................................................................................................................................... 31
Female Economic Contributions and Male Participation in Domestic Chores .................... 32
Male Control Over Women ...................................................................................................... 33
Violation of Female Property and Ownership ......................................................................... 36
Female Dependency on Men .................................................................................................... 36
Who Works the Hardest ............................................................................................................ 38
i
Conclusion ................................................................................................................................ 40
7. Gender and Violence............................................................................................................. 41
Respondent Views on Gender and Cause of Domestic Violence ............................................. 42
Frequency of Violence and Protagonist .................................................................................... 42
Identity and Sex of Aggressors ................................................................................................. 43
Spousal Abuse/Violence Against of Respondent .................................................................... 44
Male Spouse Violence Against Female Respondent by Female Household Financial
Contributions............................................................................................................................. 44
Spousal Violence (Against Respondent) and Degree of Urbanization ..................................... 45
Domestic Violence Against the Respondent vs. Socio-Economic Status................................. 45
Reasons for Violence Against Respondent ............................................................................... 47
Respondent Violence Against Others ....................................................................................... 48
Rape .......................................................................................................................................... 49
Back Ground of the Rape Epidemic ..................................................................................... 49
Estimating the Number of People Raped .............................................................................. 49
Estimating the Actual Numbers of People Raped: "Scaling-Up" ........................................ 51
Network Size......................................................................................................................... 52
Respondents View on Changing Incidence of Rape ............................................................. 54
Expected Community Reactions to Rape ............................................................................. 54
Security ................................................................................................................................. 55
Security and Laws ................................................................................................................. 56
Conclusion ................................................................................................................................ 58
8. Family, Partners, Children, and Sex ..................................................................................... 59
Opinions on who is more in Need of Sex ................................................................................. 59
Appropriate Age at onset of Sexual Activity ............................................................................ 59
Teen Pregnancy......................................................................................................................... 60
Teen Pregnancy in Leogane and Carrefour Sample vs. in the United States ....................... 60
Childbirth & Conjugal Union ................................................................................................... 61
Pro-Natalism: Children and Fertility ........................................................................................ 62
Preference for Boys vs. Girls .................................................................................................... 63
Abortion and Contraceptives .................................................................................................... 65
Contraceptives........................................................................................................................... 67
9. Family Support...................................................................................................................... 68
ii
Quality of Family Relationships and Support ........................................................................... 68
Opinions on Quality of Relationships to Partner and Children ............................................ 68
Who Respondents turn to for Material Support .................................................................... 69
Who Respondents turn to for Moral Support/Advice ........................................................... 70
10. NGOs, Hospitals, and Clinics ............................................................................................ 71
Membership in Organizations ................................................................................................... 71
NGO and State Sponsored Seminars since the Earthquake ...................................................... 72
Illness and Use of Hospitals, Clinics, and Doctors ................................................................... 73
Pre-Natal, Birth and Use of Services ........................................................................................ 76
Post-Natal Care and Use of Services ........................................................................................ 78
11. Conclusion and Recommendations .................................................................................... 80
Mobilize .................................................................................................................................... 80
SEED-SCALE........................................................................................................................... 80
Identify credible partners .......................................................................................................... 81
Combat Misinformation:........................................................................................................... 81
Young Males ............................................................................................................................. 82
12. Notes .................................................................................................................................. 84
13. Annex: Questionnaire ........................................................................................................ 90
Questionnaire English ........................................................................................................ 90
Introduction ......................................................................................................................... 90
WORKS CITED ......................................................................................................................... 100
List of Tables
Table 4.1: Target Sample Size and Stratification.................................................. 12
Table 4.2: Age Groups for Actual Sample Taken................................................. 13
Table 5.1: Department of Origin........................................................................... 15
Table 5.2: Skills of Respondents........................................................................... 18
Table 6.1: Residents per Gender Household Headship Type................................ 19
Table 6.2: Population Household.......................................................................... 20
Table 6.3: Roof...................................................................................................... 21
Table 6.4: Latrine.................................................................................................. 22
Table 6.5: Water Source........................................................................................ 22
Table 6.6: Potable Water....................................................................................... 22
iii
Table 6.7: Cooking Fuel........................................................................................ 23
Table 6.8: Energy.................................................................................................. 23
Table 6.9: Monthly Educational Expenditure for Oldest Child........................... 23
Table 6.10: Average Cost of Rent (USD) ............................................................ 23
Table 6.11: Home Ownership............................................................................... 24
Table 6.12: Source of 1st and 2nd Contributor Income by Sex of Contributor... 26
Table 6.13: Sources of Income First and Second Income Provides .................... 26
Table 6.14: Sex of First and Second Income Providers by Sex of Respondent
Identified Household Head................................................................................. 27
Table 6.15: Who is the Primary Performer of Household Tasks by Sex and
Age..................................................................................................................... 31
Table 6.16: Who Has Final Say............................................................................. 33
Table 6.17: Needs to Ask Permission to Visit Faraway by Sex............................ 35
Table 6.18: Needs to Ask Permission to Join Organization by Sex...................... 35
Table 6.19: Who asks permission of Who ........................................................... 35
Table 6.20: Respondents who report that Someone Took Something from them
Since Earthquake............................................................................................... 36
Table 6.21: Respondents Who Can Live Without Spouse by Location............. 38
Table 6.22: Reasons Respondents can Live Without Spouse ............................. 38
Table 6.23: Who Respondents Say Works Hardest.............................................. 39
Table 7.1: Last Time Beaten by Sex of Respondent............................................. 42
Table 7.2: Person Who Beat Respondent the Last Time He/ She was Beaten.... 43
Table 7.3: Person who Beat Respondent: Adults Last Three Year Only............ 44
Table 7.4: Why Beaten for All Cases.................................................................... 47
Table 7.5: Why Beaten for Adults or Within Past 3 Years Only.......................... 47
Table 7.6: If Respondent Believes Beating Was Deserved.................................. 47
Table 7.7: of If Respondent Believes it Was Deserved for Adults or Within
Past 3 Years Only.............................................................................................. 48
Table 7.8: Aggression Against Others by Sex 48
Table 7.9: Identity of People Respondents Attacked 48
Table 7.8: People Who Know At Least One Person Raped Since Earthquake by
Commune.......................................................................................................... 49
Table 7.9: Respondents who Know at Least One Person Raped Since
Earthquake by Age of Respondents ................................................................ 51
Table 7.10: Respondents Who Know At Least One Person Raped Since
Earthquake by Enumerator Who Asked the Question ...................................... 52
Table 7.11: Respondents "know" anyone who has been raped since January
12th 2010 Earthquake and Number Known....................................................... 53
Table 7.12: Deriving Average Female Network Size.......................................... 53
Table 7.13: Choice of Single Biggest Criminal Problem...................................... 54
Tablet 7.14: Two Biggest Problems for Young Men ........................................... 56
Table 7.15: Two Biggest Problems for Young Women ....................................... 56
Table 7.16: When Respondents Think Last Rape Law Passed............................. 57
Table 7.17: Respondents Knowledge About Laws Regarding Raping or
Beating Girlfriend or Spouse........................................................................... 57
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Table 7.18: What a Woman Should If Raped ...................................................... 57
Table 7.19: Where A Person Can Go For Care In The Area If They Have Been
Raped................................................................................................................ 57
Table 7.20: Special Clinic for Rape Victims Mentioned...................................... 58
Table 8.1: When Should Boys vs. Girls Become Sexually Active...................... 60
Table 8.2: Children Born to Men and Women by Age and Sex 18 to 25 Years
Old..................................................................................................................... 61
Table 8.3: Percentage of Respondents per Age Groups who Have Children....... 61
Table 8.4: Whether People Need Children............................................................ 62
Table 8.5: Average of Ideal Number of Children ................................................ 62
Table 8.6: Children Born to Men and Women by Age and Sex.......................... 62
Table 8.7: Family of 3 vs. 6 Children.................................................................... 63
Table 8.8: Location of People who Favor Family of 6 vs. 3 Children................. 63
Table 8.9: Reasons for Choosing Family with 3 Children................................... 63
Table 8.10 Reasons for Preferring Girls................................................................ 65
Table 8.11:Why Boys......................................................................................... 65
Table 8.12: Frequency of Reasons For Justifiable Abortion................................ 66
Table 8.13:Tolerance for Abortion...................................................................... 66
Table 8.14: Count of Contraceptive Good vs. Bad by Sex of Respondent .......... 67
Table 8.15: Contraceptive Good vs. Bad by Age of Respondent......................... 67
Table8.16: Right to Use Contraceptives with spousal consent by Sex................ 68
Table 9.1: First Person Respondent Goes to if Needs Material Aid..................... 70
Table 9.2: Count of Need Advice ......................................................................... 70
Table 10.1: Group Membership by Type of Group and Sex of Respondent........ 71
Table 10.2: Types of Seminars Respondents Attended Since Earthquake ........... 73
Table 10.3: Seminar Sponsors............................................................................... 73
Table 10.4: Last Illness in the House ................................................................... 74
Table 10.5: Who Was Sick ................................................................................... 74
Table 10.6: Reasons Given for Not Going to Hospital, Clinic or Doctor............. 75
Table 10.7: Most Knowledgeable Illness in the House....................................... 76
Table 12.1: Selected Latin American and Caribbean Adolescent Birth Rates..... 83
Table 12.2: Formal Sector Employment............................................................... 86
Table 12.3: Mostly Informal Sector Employment ................................................ 86
Table 12.4: Entrepreneurial Sector....................................................................... 86
Table 12.5: Chi Square for Who Wins Arguments............................................... 86
Table 12.6: Respondents who Say that Woman Has Right to Beat Other
Woman or Husband if He has Affair............................................................... 87
Table 12.7: Respondents who Say that Man has Right to Beat Spouse if she has
an Affair ............................................................................................................. 87
List of Charts
Chart 4.1: Sex of Respondents.............................................................................. 13
Chart 4.2: Respondents per commune................................................................... 13
Chart 4.3: Urban vs Rural (Leogane and Carrefour)............................................. 14
v
Chart 4.4: Location of Respondents...................................................................... 15
Chart 5.1: Where Respondent Grew Up................................................................ 15
Chart 5.2: No Education........................................................................................ 16
Chart 5.3: At least 7th Grade................................................................................. 16
Chart 5.4: Comparison of Proportion of Population with no Education: Survey
Populations vs. National Data........................................................................ 16
Chart 5.5: Educational Level by Sex..................................................................... 17
Chart 5.6: Comparison of Illiterate Population by Sex and Commune................ 17
Chart 6.1: Household Type .................................................................................. 19
Chart 6.2: People per Hshld by Hshld Type.......................................................... 19
Chart 6.3: Household Types Carrefour vs. Leogane ............................................ 20
Chart 6.4: Home Ownership................................................................................. 23
Chart 6.5: Female Breadwinners........................................................................... 25
Chart 6.6: Male Breadwinners............................................................................... 25
Chart 6.7: Comparison of Proportion of Sample by Gender of 1st and 2nd
Breadwinners: Male vs. Female....................................................................... 25
Chart 6.8: Daily Food Expenditures (USD) by Gender House Type................... 28
Chart 6.9: People per Hshld by Hshld Type.......................................................... 28
Chart 6.10: Per Person Daily Food Expenditures (USD) by House Type............ 28
Chart 6.11: Statistical Significance of Household Type by Average Food
Expenditures p<05........................................................................................... 28
Chart 6.12: Average Daily Food Expenditures (USD) by Gender of Principal
Breadwinners................................................................................................... 28
Chart 6.13: Woman Manages Household Budget by Household Type................ 29
Chart 6.14: Female Manager of Budget by Gender of 1st and 2nd Contributors
of Income ....................................................................................................... 29
Chart 6.15: Gender of Who Controls the Budget by Per Person Expenditures 30
Chart 6.16: Food Expenditures Per household by Gender of Who Controls
Budget............................................................................................................ 30
Chart 6.17: Comparison of Per Person Hshld Food Expenditures by Gender
that Controls Budget and Single Male Hshld (p < .05) ................................. 31
Chart 6.18: Females Only Wash Dishes by Gender of 1st and 2nd Income
Contributors (Single Male Headed Hshlds Excluded) ................................... 32
Chart 6.19: Who Usually Wins Arguments by Sex.............................................. 33
Chart 6.20: Who Usually Wins Arguments Between Patners (for All
Respondents with partners) ......................................................................... 33
Chart 6.21: Winner of Arguments with partner by Sex and 1st and 2nd Income
Contributors...................................................................................................... 34
Chart 6.22: Must Ask Permission To Visit Family Far-Away by Sex of
Respondent ...................................................................................................... 34
Chart 6.23: Must Ask Permission to Join an Organization................................... 34
Chart 6.24: Sex of Those Who Would Visit Even If Told ‘’No’’ ........................ 35
Chart 6.25:Sex of Those Who Would Join Even If Told ``No``........................... 35
Chart 6.26: Respondents who have had Goods Taken Since the Earthquake...... 36
Chart 6.27: Which Spouse Needs the Other More: Man or Woman.................... 37
vi
Chart 6.28: "Yes" Can "Live" Without a Spouse (all respondents) .................... 37
Chart 6.29: "Yes" Can "Live" Without Having a Spouse (respondents in
union) ................................................................................................................ 38
Chart 6.30: Sex of All People Respondents Identified as Working the Hardest... 39
Chart 6.31: Sex of Respondents Self Identifying as Working the Hardest........... 39
Chart 6.32: Sex of Other People Respondents Identified as Working the
Hardest.............................................................................................................. 39
Chart 7.1: Who Respondents Believe is most Often the Cause of Male
Violence Against Women............................................................................... 42
Chart 7.2: Sex of Violent Protagonists ................................................................. 43
Chart 7.3: Woman was Beaten by her Spouse by First and Second
Contributors of Household Income ................................................................. 45
Chart 7.4: Domestic Violence by Urbanization (City, Countryside, Peri-Urban) 45
Chart 7.5: Domestic Violence by Urbanization (Countryside vs Peri-Urban &
City) ................................................................................................................. 45
Chart 7.6: Mean Household Monthly Educational Expenditures on Oldest
Child by Aggressor in Last Incidence of Domestic Violence......................... 46
Chart 7.7: Beaten by Spouse or Lover by Type of Roof ...................................... 46
Chart 7.8: Type of Household Latrine by Last Incidence Domestic Violence.... 46
Chart 7.9: Respondents Evaluations of Rape Before vs After Earthquake........... 54
Chart 7.10: For Which Family is the Shame Greater: Victim or Rapist.............. 55
Chart 7.11 Most Likely Reactions to a Rape in the Neighborhood ..................... 55
Chart 7.12: Percentage of Respondents Who Know Nothing of Rape Law........ 56
Chart 7.13: Comparison in Quality of Services for Rape Victims: Before vs
AfterEarthquake............................................................................................... 58
Chart 8.1: Who Needs Sex More, Men vs. Women by Sex of Respondent........ 59
Chart 8.2: Comparison of Statistical Significance for Average Number of
Parent-Partners if Respondent Has Children: Men vs.Women ...................... 61
Chart 8.3: Respondents who Say a Family with 3 vs. 6 Children is Better Off.... 63
Chart 8.4: Family with 3 Girls vs. 3 Boys (All Respondents)............................... 64
Chart 8.5: Preference for Family with 3 Girls vs 3 Boys (Female)....................... 64
Chart 8.6: Preference for Family with 3 Girls vs 3 Boys (Male).......................... 64
Chart 8.7: Analysis of Age by Tolerance of Abortion......................................... 66
Chart 8.8: Proportion of Respondents Qualifying Contraceptives as "Mostly
Good" (Female Respondents.......................................................................... 67
Chart 8.9: Proportion of Respondents Qualifying Contraceptives and "Mostly
Good" (Male Respondents ................................................................................... 68
Chart 9.1: How Women and Men Rate Relationship with Their Partner............. 69
Chart 9.2: How Women and Men Rate Relationship with Their Children........... 69
Chart 10.1: Member of At Least one Organization (Including Church)............... 71
Chart 10.2: Member of At Least one Organization (Excluding church) .............. 71
Chart 10.3: At Least One Official Position in an Organization............................ 72
Chart 10.4: Attended At Least One Seminar Since Earthquake............................ 72
Chart 10.5: Number Seminars Respondents have Attended Since Earthquake... 72
Chart 10.6 Attended At Least One Seminar Since Earthquake............................. 72
vii
Chart 10.7: Attended At Least One Seminar Since Earthquake by Sex and by
Commune......................................................................................................... 72
Chart 10.8: Symptoms/Disease When Person Was Last Sick............................... 74
Chart 10.9: Where the Person was Treated........................................................... 75
Chart 10.10: Use of Hospital for Last Illness in the House: Carrefour vs
Leogane .......................................................................................................... 75
Chart 10.11: Pre-Natal Care: Where Respondent Consulted Last Time She was
Pregnant............................................................................................................ 76
Chart 10.12: Use of Pre-Natal Services: Carrefour vs. Leogane .......................... 77
Chart 10.13: Reasons Respondent Did Not Consult Last Time Pregnant ........... 77
Chart 10.14: Birth at Home: Carrefour vs. Leogane ........................................... 77
Chart 10.15: Post Natal Care: Where Respondent Consulted Last Time Gave
Birth ................................................................................................................ 78
Chart 10.16: Use of Post-Natal Services: Carrefour vs. Leogane ........................ 78
Chart 10.17: Respondents who did not use any Post-Natal Specialist Last
Pregnancy: Carrefour vs. Leogane (p < 95%) ................................................ 79
Chart 10.18: Post Natal Care: Why Respondent did not Consult at Clinic or
with Doctor....................................................................................................... 79
viii
1
Summary of Important Findings
• Urban based Single Female-Headed Households appear to be materially better off
than households where both a male and female head is present; this is true on
every count, be it construction, quality of latrine, or access to electricity and water
(the reference here is to households; no IDP camps fell into the selected sample
areas).
• Rural based Single Female-Headed Households tended to be on par with Male-
Female Headed Households.
• Women are usually in control of household budgets, even when they are not
among the primary financial contributors to the household.
• Women more often than men win arguments with their spouse, something
respondents report no matter who the respondent is, man or woman.
• Men, more than women, feel the need to ask permission of someone in the
household to travel or join an organization; and if told no, women are more likely
than men to go or join anyway.
• All household members, including males, more often defer to women for
permission to travel or join an organization.
• A very small percentage of both women and men condone, or believe that
violence against women is justifiable or legal, even in cases of infidelity.
• More people believe that women are the cause of male violence against women
than vice versa, something pronounced among men but even among women 49%
felt that women usually incited male violence.
• Males suffer greater violence in terms of physical beatings; this is true both for
children and adults.
• At least 12% of women report having been beaten at least once by their spouse.
• Rape occurs far less frequently than we have been led to believe by a series of
high profile reports from specific grassroots gender based activist organizations
and activist-scholars and journalists working in Port-au-Prince.
• Respondents overwhelmingly report that in terms of material survival (vis a vis
the household), men are "more dependent" on their wives than vice versa.
CARE Leogane & Carrefour Gender Survey 2
1. Overview
The quantitative Gender Survey described in this document was part of a larger evaluation and
exploration of gender in Leogane and Carrefour, two communes (counties) near to Port-au-
Prince that were among those most heavily impacted by the January 12th 2010 earthquake.
Following the catastrophe CARE initiated emergency and supportive relief efforts in the
communes, including sanitation, health and cash for work programs. In April 2010 CARE
launched a program on Sexual and Reproductive Health (SRH) focusing on family planning and
maternal health; later that same year CARE added the Life-Saving Interventions for Women and
Girls project, the objective of which was to "combat gender-based violence and to reduce
mortality and morbidity among earthquake-affected women and girls." In March 2013 CARE
commissioned the qualitative evaluation of these projects and the present complementary
quantitative survey that would help to both corroborate findings from the qualitative evaluation
and provide guidance for further gender-informed interventions in the region. Both studies are
part of CARE International's commitment to helping the poor in Haiti and to long term
development, endeavors in which it has been a major Government of Haiti ally since 1954.
CARE recognizes that effective development interventions depend on relevant up-to-date
information. CARE also recognizes that gender behavior within Haiti varies across
socioeconomic strata, educational level, urban versus rural social settings, and with respect to
differential male versus female control over resources. With this in mind, the proposed study was
meant to clarify,
• Differences in rural and urban attitudes toward fertility
• Views about Age of sexual debut and teenage pregnancy and abortion
• Household decision-making (who, why)
✓ Use of finances
✓ Condom, contraceptive use
✓ Healthcare seeking
• Domestic violence
• Gender based division of labor
• Awareness about new rape laws
• Stigma toward rape victims and effectiveness of post-rape care system
• Exposure to violence and sexual abuse (partner, criminal activity)
• Impact of differential female economic status and resources
✓ Support systems, social cohesion
• Norms and expectations within conjugal unions regarding freedom of
women to travel and participate in community activities
• Economic status of female and male headed households
CARE Leogane & Carrefour Gender Survey 3
Image 2.1: Haiti, the Communes of Leogane and Carrefour,
and the Selected Survey Sample Points
Commune of
Carrefour
-Est. pop = 500,000
-Area = 165 sq. km.
Commune of Leogane
-Est. pop = 190,000
-Area = 385 sq. km
(Population derived from: Ambassade d'Haïti, Washington D.C.; Posted on Geohive
http://www.geohive.com/cntry/haiti.aspx. Above estimates are modified for population growth to
yiled 2012 estimates.)
CARE Leogane & Carrefour Gender Survey 4
2. Review of the Literature
We begin with a review of past ethnographic research and surveys that focused on gender in
Haiti. Understanding the observations made by others before helps in identifying enduring
features of gender in Haiti, patterns of change and, not least of all, the shortcomings and bias that
has infected our work. It was this past research that informed the design of the current study.
Our hope is that by using it as a guide we can preserve or enhance those interventions that have
been well targeted and appropriate and, in the endeavor to make better and more efficient use of
resources while helping those in need, better target future interventions.
Gender in Haiti is and long has been highly patterned and distinct from the more patriarchal
trends found in neighboring Cuba, the Dominican Republic, and many African societies among
which development and academic programs frequently classify Haiti. These patterns include
female monopoly of most household productive enterprises (such as food harvesting and
processing), a high degree of female control over the homestead, and a nearly complete female
monopoly over intermediate level redistribution and marketing of agricultural produce, small
livestock, and fish (three of provincial Haitian households four main sources of income from
production; the fourth source is charcoal produced for the urban market). Women have
traditionally been considered the principal owners of homes, they are the primary disciplinarians
of children, and their male partners often depend heavily on them as managers of the homestead.
Undergirding the prominent role of women in organizing household labor and selling the
products of the homestead is the fact that for many people in Haiti the homestead – be it urban or
rural – is the single most important and often the only means of social and material security in
what is an unforgiving region of the world characterized by catastrophic weather patterns and
unpredictable economic crises (for past descriptions from anthropologists see Herskovits 1937;
Simpson 1942; Metraux 1951; Murray 1977; Smucker, 1983; Schwartz 2000).
In the traditional rural Haitian society that to a large degree continues to dominate Haitian
cultural expectations, the sexual division of labor and female primacy in governing economic
matters of the popular household were linked to distinctly patterned gender rights and duties.
Men were considered the financiers and underwriters of female entrepreneurial activities and
household expenses; men gave women money; it was the woman's right to receive; women were
expected to reciprocate with sex and domestic service while intensely engaging in their own
privately owned and managed marketing businesses the proceeds of which were intended for the
maintenance of the household and children. If a man did not meet his obligations, the woman,
even if married, had a socially recognized right to look for male support elsewhere (ibid; also
note that all that has so far been described are in fact gender patterns that until recently prevailed
throughout the non-Hispanic Caribbean; see for example Mintz 1955, 1971, 1974; Cohen 1956; R.
T. Smith 1956; Solien 1959; Davenport 1961; M.G. Smith 1962; Kundstadter 1963; Otterbein 1963,
1965: Clarke 1966; Greenfield 1961; Walker 1968; Rodman 1971; Pollock 1972; Philpott 1973;
Buschkens 1974; Durant-Gonzalez 1976; Hill 1977; Berleant-Schiller 1978; Massiah 1983; Griffith
1985; Olwig 1985; Gearing 1988; Handwerker 1989; Brittain 1990; Lagro and Plotkin 1990; Senior
1991; Mantz 2007 ).i
CARE Leogane & Carrefour Gender Survey 5
The popular class Haitian gender patterns being described were and in popular class continue to
be manifest in what anthropologist Ira Lowenthal (1987) called a 'field of competition' between
the sexes. Women are taught to think of themselves as able to get along without sexual
gratification while conceptualizing their own sexuality in terms of a commodity, referring to
their genitals as intere-m (my assets), lajan-m (my money), and manmanlajan-m (my capital), in
addition to tè-m (my land). A popular proverb is, chak famn fet ak yon kawo te—nan mitan janm
ni (every women is born with a parcel of land—between her legs). Men on the other hand are
taught to believe they need sexual interaction with women and chastised for not making material
overtures to women. Called “gendered capital” by Richman (2003: 123), these sexual-material
values continue to be universal in the popular classes and apply whether the woman in question
was dealing with a husband, lover, or more causal relationship. The consequence is an ongoing
socially constructed and sexually intoned negotiation between men and women in which material
advantage accrues to women.
However, love, devotion, sex, and domestic service for material gain should not be equated with
prostitution, promiscuity or subservience. Although influenced by family, particularly mothers,
95% and more of all women in the 2005-06 EMMUS reported selecting their own spouse and
their subsequent comportment is embedded in a system of restraint and censorship such that
sexual modesty in Haiti is, in terms of reporting and statistical norms, more conservative than
found in mainstream US society. For example, while 20.7% American adolescent girls 15 to 19
years of age report having 2 or more sexual partners in the 12 months prior to being interviewed,
only 1.6% of Haitian adolescents girls report the same (National Health Statistics Reports 2011;
EMMUS 2012). American women 40 to 44 years of age report 3.4 lifetime sexual partners;
Haitian counterparts report 2.5 (ibid; 2005-6 EMMUS). Even Haitian men--who few observers
have would describe as sexually conservative--come off as modest in comparison to American
men: the 2005-06 EMMUS found that 45% of single Haitian men 15 to 24 years of age reported
not having sex in the previous year. The figure for abstinent US men in the same age group is 33
percent (National Health Statistics Reports 2011). As for subservience, Haitian women are
better described not as timid and demure servants to men, but rather as outspoken, aggressive,
and even violent defenders of the gender defined economic rights seen above (see Gerald Murray
1977; Schwartz 2000; and see James 2006 for some rich examples of violent Haitian female
"viktim").
This description, of what can be called Haiti's traditional popular class "sexual moral economy" -
-a description drawn largely from the ethnographic literature and supported by the highly
regarded Demographic and Health Surveys (EMMUS2005-2006 and 2012)--is incomplete
without noting that it has been historically accompanied by a strong, socially reinforced desire to
parent children, what can be called radical pronatalism. The trend is such that the observation
anthropologist George Simpson (1942: 670) made 60 years ago, 'that the Haitian peasant wishes
to have children, and to have the largest number possible,' was applicable 35 years later, in 1977,
when anthropologist Gerald Murray did two years of research in Haiti's Cul-de-Sac; it was
applicable in 1987 when anthropologist Ira Lowenthal summarized his four years of research on
the Southern Peninsula; it was still largely applicable in 1996 when Anthropologist Gisele
Maynard Tucker summarized her 2,383 household survey of men and women in both urban and
rural areas of greater Port-au-Prince; it was applicable in 1998 when Jenny Smith reported from
CARE Leogane & Carrefour Gender Survey 6
two years of research on Haiti's Plain du Nord; and certainly still applicable when the author
(Schwartz 2000) reported on five years of research in Haiti's Northwest (Schwartz 2000). Linked
to radical pronatalism are an abhorrence of abortion; a wide array of beliefs that associate
contraceptives with illness and promiscuity; and superstitions and folk beliefs that seem exotic to
outsiders but that promote high fertility. The latter include a firm belief in spells that make
people fall in love, that having sex with an insane or handicapped woman brings luck, the fictive
illness known as perdisyon wherein a fetus can gestate in a woman's womb for as long as 5
years (technically known as "arrested pregnancy syndrome"), and superstitious rationales that
convince men to accept paternity for children that are not biologically their own, such as the
widely accepted blood test--the belief that if a man pricks his own finger and puts a drop of
blood on the newborn‘s tongue he can determine if the child is his, for if he is not the father the
baby will die instantly. (For descriptions of the aforementioned see Herskovits 1937; Simpson
1942; Murray 1977; Smith 1996; Maternowska 2006; and Schwartz 2009.)
Despite the long history of in-depth anthropological studies cited above, many outsiders
(including among them some notable Haitian intellectuals) have misunderstood gender in Haiti
and by corollary their relationship to the described pronatal patterns and folk beliefs. Many of the
scholars imposed patriarchal models that apply to other countries or that are logical in the
context of traditional middle and upper class Western value systems but that do not fit popular-
class social patterns in Haiti. For example, in a stark misinterpretation of rural life in Haiti first
noted by Gerald Murray (1977: 263), the oft-repeated explanation for polygyny has long been
that farmers use “extra” wives to tend additional gardens (Bastien 1961: 142; Courlander 1960:
112; Herskovits 1937; Leyburn 1966: 195; Moral 1961: 175–76; Simpson 1942: 656). As
Murray pointed out, this is not now and probably never was true. Women in rural Haiti do not
work in gardens on behalf of men. On the contrary, they may sometimes work gardens on their
own and their children’s behalf, but when a man is present the obligation to plant and weed falls
to him (Murray 1977; Smucker 1983; Schwartz 2009). Indeed, a tradition so consistent over the
years that it can be elevated to the status of a cultural rule is that Haitian women, not men, are
considered the owners of the household agricultural produce; produce largely cultivated by the
efforts of male household members (ibid).
The same tendency to misconstrue or impose outside gender patterns onto popular class Haiti
prevails today, particularly among foreign analysts, international social activists, and aid
workers. Several notable exceptions notwithstanding (N’zengou-Tayo 1998, Fafo 2004, Gardella
2006), most present repression of women as worse in Haiti than other countries. In doing so they
cite discriminatory legal codes (Fuller 2005; UNIFEM 2004), political violence against women
(Fuller 2005; UNIFEM 2004), high levels of mortality during childbirth (UNIFEM 2004; World
Bank 2002), the feminine struggle for identity manifest in creative literature (Francis 2004),
female involvement in onerous, labor-intensive economic endeavors (Divinski et al. 1998), and
even the overall deterioration of economic and political conditions (UNIFEM 2006).
Summarizing these views, the UN’s Gender Development Index (GDI) ranks Haiti at the very
bottom of the Western hemisphere, making it seem to observers who do not carefully interpret
the index that Haiti is the most female repressive country in all of Latin America, indeed the
world, considerably lower in ranking than Iran or Saudi Arabia (United Nations Development
Programme 2006).
CARE Leogane & Carrefour Gender Survey 7
A good example of how far from fact many feminist presentations have gone is the work of
Beverly Bell, one of the more outspoken experts on gender in Haiti and author of the acclaimed
book Walking on Fire (2001). In the introduction to her book Bell claimed that,
“Haitian women place at the absolute bottom in female-male life expectancy differential,
incidence of teen marriage, contraceptive use, primary school enrollment, secondary school
enrollment, and ratio of secondary school teachers. They tie for worst or rank second to
worst in the following: economic equality with men, social equality, life expectancy, rate of
widowhood/divorce or separation, University enrollment, female adult literacy, discrepancy
between male and female literacy...” [Bell 2001: 18]
Bell was wrong on every count. At 63 vs 59 years, women in Haiti live longer than men (UN
2010); at 43 per 1,000 babies annually born to adolescent girls 15 to 19 years of age, Haiti's teen
pregnancy rate is officially among the lowest in the developing world, half or less that of many
Latin American countries, including the neighboring Dominican Republic (World Bank 2013;
WHO 2007; UNFPA 2007; WHO 2001) and one third the 2006 rate of 126 for both Hispanic and
Black youth in the United States (Planned Parenthood 2011).ii In both urban and rural areas
more Haitian females have finished primary school than males (86.6% to 85.2% for urban areas
and 73.2% to 72.4% in rural areas) and more urban based females have completed secondary
school (41.9 %to 39.1%). Only with regard to completion of secondary school in rural areas do
boys prevail (20.0% to 11.7%: see EMMUS 2012). Indeed, for those concerned about gender
differential treatment of children a good case can be made that it is Haitian boys, not girls, who
are in need of special attention: in addition to the educational differences favoring girls, the
2005-06 EMMUS found that chronic malnutrition was significantly greater among boys (25%
vs 20%: p.162); the same was true for child mortality (143/1,000 boys to 132/1,000 for girls 0 to
62 months of age: p. 86).
Returning to Bell and the contemporary status quo for the presentation of gender in Haiti, the
only point that she seems to have gotten right is that, as seen earlier, it is true that Haitian
women, particularly rural women, eschew contraceptives. Despite massive and costly
internationally funded contraceptive campaigns extending back in time back to the early 1970s,
only 28.7% of reproductive aged Haitian women were using them in 2010; that translates to the
lowest contraceptive use rate in the Western hemisphere; 7.6% lower than the next lowest rate:
Bolivia at 36.3% (see Alkema et. al. 2013). But there is little evidence that low female
contraceptive use in Haiti has anything to do with male domination. In the 2005-06 EMMUS
only 2.3% of reproductive aged Haitian women interviewed reported not using modern
contraceptive because their spouse objected (p. 73).iii
Perhaps the most interesting feature of the misrepresentation of gender status in Haiti is precisely
the point touched on above: that the notion of Haitian women as "viktim" and under the control
of their spouses has prevailed despite the fact that the EMMUS studies--the most relied on
source for demographic, reproductive health and gender data for Haiti--provide extensive
evidence to the contrary. An overwhelming proportion of women interviewed for the Haiti
EMMUS's report having or sharing the final word on household issues ranging from large and
CARE Leogane & Carrefour Gender Survey 8
small household expenditures, to work habits, child discipline, education, and health (EMMUS
2005-6; p 245 - 250). Moreover, the trend is not, as many observers seem to assume, one of the
poorest women suffering the most severe repression. The authors of the 2005-2006 EMMUS
noted that,
Against all expectations, we find that women who most frequently participate in making the
seven decisions inquired about are rural women and those who have less education. [And]
Women who work for money are [also] involved much more frequently than others in
decision making.iv v [EMMUS 2005-6: 247]
Reinforcing the erroneous or at least ethnographically and statistically unsupported image of
Haitian women as, by global standards, economically, physically, medically, and socially
repressed vis a vis men, are claims that they suffer extreme physical and sexual violence at the
hands of their male spouses, criminals, paramilitary thugs and even police. Since the 2010
earthquake this image has been especially prominent in reports from grassroots activist
organizations, human rights organizations, NGOs, the UN, and the international press (Bell
2010; Faul 2010; KOFAVIV 2010; Amnesty International 2011; Kolbe et. al. 2010). For
example, following the earthquake grass-roots activist organizations were reporting such a high
incidence of rape that the international press labeled it "epidemic."
It would seem that at least some support for the image of Haitian women suffering extraordinary
domestic violence comes from the EMMUS studies. The 2005-6 Haitian EMMUS found that
19.3% of women interviewed had, at some point in their lives, experienced physical or sexual
violence at the hands of a partner. However, putting this in regional perspective, it is the second
lowest rate in Latin America (PAHO 2012); and 2.8% lower than the 22.1% rate reported in the
United States for year 2000 (Tjaden and Thoennes 2000).
Moreover, what we do not learn from the EMMUS interviews is what men report about female
violence or to what extent women may sometimes be more accurately categorized, not as passive
victims, but as combatants. The EMMUS did not interview men regarding female violence. At
least some anthropologists report that Haitian women are in fact physically assertive and as or
more violent than male counterparts with respect to both other women and men (Murray 1977;
Schwartz 2000). If true, the observation should arguably not come as a surprise. Given the high
degree of economic engagement and the conspicuous role of popular class Haitian women in
household and family decision-making processes a high degree of assertiveness can be expected
in both defending and exerting their entrenched and socially recognized rights. In the surveys
discussed in this report, women who reported experiencing domestic violence were in fact more
likely be among those who made significant economic contributions to the household. As for
reports of epidemic levels of post-earthquake extra-domestic rape and violence against women:
we found no evidence in the Leogane and Carrefour surveys to support the claims.
Returning to the trend in the literature of misrepresenting Haiti's popular class gender patterns,
not all scholars have overlooked the prominence and high degree of de facto male-female equity.
In her 2006 Gender Assessment for USAID, Gardella emphasized that Haitians show no gender
CARE Leogane & Carrefour Gender Survey 9
preference in educating their children. The Understanding Children’s Work Project (2006),
drawing on EMMUS 2005-6, concluded that Haitian boys more often than girls work outside the
home, they work harder than girls, and they work for longer hours than girls. In terms of adult
female participation in the work force, Haiti is second only to Lesotho as that developing country
with the highest rate of female economic participation; in 1995 the Inter-American Development
Bank (IDB) estimated male vs. female participation rates at 87% and 62%, respectively (IDB
1999). Moreover, there is at least some strong evidence that rural female headed households may
be better off--or at least not as badly off--as their male counterparts: Sletten and Egset's (2004)
found that 28% of rural households are headed by women and 72% are headed by men; but four
times as many rural male-headed households face "extreme food insecurity." In the surveys
discussed in this report we found that in both rural and urban areas Single Female Headed
Households were materially as or better off than those households with both a male and female
head.
None of this to say that there are not serious gender issues that should be addressed. Haitian
gender patterns have been widely misunderstood. But times are changing. Haiti has gone from
95% rural in 1950 to 60% rural in 2000. The year 2009 marking the first time that Haiti was as
urban as it was rural (World Bank 1995; CIA 2005). In the three years since the earthquake the
urban population has shot to 55 percent (World Bank 2013). This means that a large portion of
the Haitian female youth is no longer being reared in an ambience where they can look forward
to the traditional female dominated rural marketing system as a means to economic autonomy.
Nor will they have the socially defined rights to control household production--specifically, the
traditionally defined female ownership of household agricultural produce. Greater physical
presence of men --i.e. less male transience with urban employment--and greater dependency on
male dominated wage labor also seems to bode a loss of power and prestige for women. And
indeed, while it was seen above that in rural areas there are dramatically fewer "extremely poor"
female vs. male-headed households, other researchers report the opposite in the urban
environment. Gardella (2006) noted that 26 percent of female headed households in Port-au-
Prince are "extremely poor" vs. 17 percent of those headed by males. While we did not find
similar results in the present survey, associated with this disparity is the fact that the single most
powerful predictor of household economic status in Port-au-Prince is if the household head has a
salaried job in the formal sector, an area where men outnumber women by a factor as high as 3 to
1 and where men monopolize the upper income strata (Sletten and Egset, 2004:14; Charmes
2000; Gardella 2006:11). With all that said, we hope that findings in this report present a
sobering perspective on gender relations in Haiti and insight into how they are changing so that
we might better prepare for an uncertain future.
CARE Leogane & Carrefour Gender Survey 10
3. Questionnaire
The questionnaire was designed with two overriding goals in mind,
1) Ask questions that encourage honest and accurate responses
2) Gather information that puts Haitian gender roles in cultural perspective
To achieve these objectives we formulated questions to be as gender neutral as possible; and,
wherever logical, we asked the same questions about men as we did about women.
The questionnaire was inspired by CARE Gender Kit (2013) and a series of cross-cultural gender
scales. Specifically, we drew on Horizons and Promundo's Gender-Equitable Men (GEM), Scale,
(Pulerwitz and Barker 2008). Schuler, Hashemi, and Riley's (1997) Women's Empowerment
Scale, Waszak, Severy, Kafafi, and Badawi's (2000) Gender Norm Attitudes Scale, Stephenson,
Bartel, and Rubardt's (2010) Gender Relations Scale, Leon and Foreit's (2009) Household
Decision-Making Scale, and Pulerwitz, Gortmaker, and DeJong's (2000) Sexual Relationship
Power Scale (for a summary of each scale see Nanda 2011)
Many of the 'cross-cultural' questions seemed inherently bias in their formulation, encouraging
us to make modifications. For example, rather than asking "Who needs sex more, men or
women?" the Gender Equitable Men (GEM) Scale asks, "Do men need sex more than women
do?" Wherever possible we made such questions gender neutral. Where the GEM Scale asks, "If
it is the woman's responsibility to avoid getting pregnant" we relied on less direct questions to
frame the structure of control over a woman's reproduction, such as "under what conditions is
abortion justifiable?" and "if a man/woman has the right to use contraceptives without informing
their spouse?"
From the Women's Empowerment Scale (WES) we took the questions 'has family taken
something from you,' 'are you free to visit family', 'freed to join organizations,' 'do you own
possessions privately', 'what is your role as contributor of resources,' and 'who performs specific
household chores.' Most of these questions were modified for ease of applicability. For example
rather than asking exactly how much a woman contributed we asked "who was the first and
second most important contributor of household support?" And once again we tried to frame the
questions so that they were gender neutral: where WES poses the question, ' a real man produces
a male child (rather than a female)?' we sought to determine child preference by posing the
situational question, "a couple with three girls vs a couple with three boys, who is better off?"
We drew one question from the Gender Norm Attitudes Scale. Specifically, "when a child is sick
who usually knows better what to do? Father, mother, same" In this case we modified the
question to fit the particular household and to capture all people in the household, a decision
encouraged by knowing that in Haiti it is often the grandmother or another family member who
prevails in the case of important household decisions. Specifically, we asked, "when one of the
children in the house is sick who knows best what to do?"
CARE Leogane & Carrefour Gender Survey 11
We were inspired by two questions from the Gender Relations Scale: "a man can hit his wife if
she will not have sex with him?" and "a woman should be faithful and have sex with her husband
even if her husband has another wife or lover?" We tried to take the hint of female bias out of
these questions by posing instead the hypothetical situation of, "what a woman should do if her
husband was having a sexual relationship with another woman?" and we tried to make it gender
neutral by also asking "what a man should do if his wife was having an affair?"
We were inspired by the Household Decision-Making Scale question, "who usually makes
decisions about making major household purchases?" We asked the exact question. We also
added, "who manages the household budget?" And finally we were inspired by the Sexual
Relationship Power Scale (SRPS) situational questions, "my partner does what he wants, even if
I do not want him to?" and "I do what I want even if my partner does not want me to?" We also
borrowed verbatim the question, "When my partner and I disagree (1) he usually gets his way, 2)
we usually compromise, 3) I usually get my way)."
Training and pretests
Our 14 enumerators, two supervisors, data monitor and the consultant engaged in three day
training and exchange of ideas to refine of the questionnaire. We performed three pretests for a
total of 195 pretested questionnaires. After each test we reviewed the questions, corrected errors,
modified content, perfected our understanding of the questions and shared experiences and
insights into the manner in which we elicited responses.
Ethical Review
We evaluated the questionnaire in lieu of admonishments in the CARE Gender Tool Kit (2013)
and the two major post-earthquake gender studies, one approved by US University of Michigan
School of Social Work (Mortality, Crimes and Basic Needs Assessment) and the other approved
by a collection of five of Haiti's most active and respected feminist organizations (POTOFI
2012). University of Michigan School of Social Work approved a series of studies in Haiti by the
Geneva Small Arms Survey (see Kolbe et. al.) that include visiting people in their homes, asking
respondents if anyone in the household had been raped over a specified period of time and then,
if the response was yes, inquiring about intimate details of the assault, including specifics of
penetration. The POTOFI Study identified pregnant teenagers and asked them intimate questions
regarding how they became pregnant, including whether or not they had been raped and under
what circumstances. The present survey did not ask intrusive questions about the sexual behavior
or traumatic sexual experiences of the respondents or household members (nor would we expect
welcome compliance or forthcoming and honest responses). Before each survey enumerators
read an explanation of the survey and respondents sign a consent form.
CARE Leogane & Carrefour Gender Survey 12
4. Methodology
The survey design was a 1,600 residences random and systematically selected cluster sample,
stratified for women vs. men and age.
Clusters, Selection, and number of respondents: A cluster was defined by the closest 24
residences to random and systematically selected latitudinal and longitudinal coordinates. The target
number of clusters was 36; with 24 respondents per cluster. In each cluster surveyors sought to
identify 3 respondents for each of the 8 age and sex categories (see Table 4.1). The number of
clusters selected and respondents interviewed per cluster conforms to the USAID Feed the Future
(2012) recommended clusters selected (36+) and WHO ideal number of respondents per cluster
of 20 to. Because of the rugged terrain and bad weather in Leogane, 7 clusters chosen in
mountainous areas were replaced with points randomly selected in low lying areas .
Table 4.1: Target Sample Size and Stratification
Age Male Female Total
18-25 100 100 200
26 - 35 100 100 200
Carrefour 36 - 50 100 100 200
50+ 100 100 200
Total 400 400 800
18-25 100 100 200
26 - 35 100 100 200
Leogane 36 - 50 100 100 200
50+ 100 100 200
Total 400 400 800
Total 800 800 1600
Image 4.1: Carrefour is on the left and Leogane on the right. The yellow waypoint markers
are selected sample points. The blue markers are the actual sites visited.
CARE Leogane & Carrefour Gender Survey 13
Respondents per Residence, Absenteeism and Replacement: Enumerators interviewed one
respondent per residence. In cases of absenteeism or failure to locate enough respondents for each
category within a cluster, additional 'nearest' houses were included in the cluster sample. For the sake
of logistical expediency enumerators sometimes moved on to other clusters without having
interviewed respondent quotas. To account for shortfalls additional clusters were added at the end of
both Leogane and Carrefour surveys. The total number of clusters actually visited was 41 in Carrefour
and 36 in Leogane. Total respondents for all age categories, both sexes and in each of the two
communes is given in Table 4.2 and Charts 4.1, 4.2.
Table 4.2: Age Groups for Actual Sample Taken
Age Groups
Sex of Sum of
Respondent 18 to 25 26 to 35 36 to 50 50 + Missing Total
Female 203 205 200 203 9 820
Male 201 204 209 204 19 823
Grand Total 404 409 409 407 28 1629
Date and duration of survey: Training and surveys began April 15th and were completed
May 15th.
Team Structure and logistics: The teams were structured in male and female team-pairs.
There were seven team-pairs. They traveled by motorcycles; one two person male-female team-
pair per motorcycle. One supervisor and the consultant also traveled by motorcycle. The other
supervisor traveled by four-wheel drive vehicle. The data monitor--who only visited base camps-
- traveled most often on public transportation. Enumerators and supervisors slept at base camps
located at each of the two sites.
Interviews and data monitoring: Female enumerators interviewed female respondents and
male enumerators interviewed male respondents. Two supervisors and the consultant monitored
performance and cluster selection. Review of the accuracy of cluster selection and data was
compounded and reviewed daily. A data monitor telephoned 10% of all respondents interviewed
CARE Leogane & Carrefour Gender Survey 14
and verified the interviews; 67% of those called were reached, a figure that corresponds with our
findings on other surveys. The reason for 33% not being reached had to do with telephone
service, no response and small portion (5%) of errors in telephone numbers, wrong names and
surveyors being given the number of a neighbor or friend of the respondent who was unaware of
what we were inquiring about. The frequency of all the preceding falls well within the bounds of
what we have found on prior surveys.
Non-Responses
There were a total of 12 people who refused to be interviewed; 6 interviews were prematurely
ended because of poor communication or disruption from other sources.
Equipment and software: The survey instruments were Samsung Galaxy tablets with
questions loaded into ODK software platform. The app program GPS Essentials was
downloaded onto each tablet and used to locate the pre-selected longitudinal and latitudinal
coordinates (preselected on Google Earth). Excel and SPSS software were used during analysis.
Sample Stratification: As seen the survey sample was pre-stratified for age and sex. We also
included an urbanization component, trying to make sure that we captured enough rural and peri-
urban respondents in Leogane to compare with heavily urbanized Carrefour (see Charts 4.3, 4.4).
Chart 4.3: Urban vs Rural
600
(Leogane and Carrefour)
63%
500
400 45%
40%
36%
300
Carrefour
200 Leogone
15%
100
0
Countryside Peri-Urban City
CARE Leogane & Carrefour Gender Survey 15
Chart 4.4: Location of Respondents
45%
40% 38% 38%
35%
30%
25% 23%
20%
15%
10%
5%
0%
Countryside Peri-Urban City
5. Respondent Profiles: Origin, Urban vs Rural, Work and Education
We begin the summary of findings with a basic demographic description of the people
interviewed. Haiti's is currently characterized by a high rate of rural to urban migration. The
trend was evident among survey respondents (Chart 5.1). Twenty-four percent of respondents
came from outside the Department of the West, where Leogane and Carrefour are located. There
were at least five respondents from each one of Haiti's ten Departments (Table 5.1).
Table 5.1:
Chart 5.1: Where Respondent Grew Up Department of Origin
70% 65% Num. of
60% Department Respondents
60% 55%
45% North East 5
50% 40% North West 8
40% 35% Central 10
30% North 19
Artibonite 30
20%
Nippes 45
10% Grand Anse 58
0% South 106
Female Male Total South East 120
Elsewhere Here West 1242
Total 1,643
CARE Leogane & Carrefour Gender Survey 16
Respondents also exhibited high levels of illiteracy characteristic of elsewhere in Haiti (Chart
5.3). However, rates of male vs. female educational attainment were, in contrast to the national
rates, skewed in favor of males: only 16% of men in the samples had never attended school
versus 25% of women (Charts 5.2); 59% of males vs. 46% of females had finished the 7th grade
(Chart 5.3). In comparison, the national average for illiteracy among adult females is 22.3 %; and
for males 23.3% for a total illiteracy rate of 22.8% (EMMUS 2012). A greater proportion of the
sample in Leogane versus Carrfour were found to be illiterate (Chart 5.4). The relationship was
pronounced for both sexes: the difference for women being 19% in Carrefour vs. 31% in
Leogane, and the difference for men being 9% in Carrefour and 23% in Leogane (Chart 5.5 &
5.6). The difference in number of women versus men who are illiterate within each commune is
also pronounced: 10% more Carrefour women versus men were found to be illiterate; 8% more
Leogane women versus men were found to be illiterate. All these relationships were statistically
significant (Chart 5.6).
Chart 6.1:
5.2: No Education Chart 6.2:
5.3: At Least 7th Grade
Male
Female
16% Female Male 46%
25% 59%
Chart 5.4: Comparison of Proportion of
Population with no Education:
30%
Survey Populations vs. National Data
25%
25% 22% 23%
20%
16%
15%
10% Female
5% Male
0%
Leogane and Carrefour National EMMUS (2012)
CARE Leogane & Carrefour Gender Survey 17
45% 41%
40% Chart 5.5: Educational Level by Sex
36%
35%
Female Male
30%
25%
25%
20% 18%
16% 16% 16%
15% 13%
9% 10%
10%
5%
0%
No Education 1st thru 5th 6th Grade 7th thru 11th 12th Grade or
greater
Chart 5.6: Comparison of Illiterate Population by Sex
and Commune (p < .05)
40%
35%
Fem Leogane,
30% 31%
25%
20% Fem Carrefour,
19% Male Leogane,
15% 23%
10% Male Carrefour,
9%
5%
0%
CARE Leogane & Carrefour Gender Survey 18
Table 5.2, lists self-identified skills as respondents reported them. But note that this data does not
refer to source of income. Some respondents overlooked their occupations and reported no skill.
For example, in Table 5.2 below 334 of 820 women reported commerce as a skill. But in Section
Six, Table 6.12, it can be seen that in 969 of the 1,643 households visited at least one resident
woman was engaged in commerce.vi
Table 5.2: Skills of Respondents
Female Male Total
Accountant 0 0 0
Police 0 0 0
Lawyer 0 2 2
Fisherman 0 3 3
Doctor 0 3 3
Communication 2 2 4
Performer 1 6 7
Traditional healer 2 5 7
Iron Worker 0 8 8
Security guard 0 9 9
Cook 13 0 13
Mason 0 17 17
Carpenter 0 18 18
Artisan 7 13 20
Teacher 10 14 24
Nurse/Medical Tech 22 2 24
Plumber/electrician 0 25 25
Baker 33 5 38
Beauticien/Barber 46 1 47
Farmer 7 48 55
Business 40 21 61
Driver 0 63 63
Computer operator 37 37 74
Tailor/Seamstress 65 11 76
Professional other 35 60 95
Commerce 334 34 368
Nothing 166 416 582
CARE Leogane & Carrefour Gender Survey 19
6. The Household
Defining Household Heads
Our investigation of gender and differential status really begins here, with an analysis of gender
specific headship and financial contributions. Respondents identified households as female or
male headed. But the category is highly subjective. For example, a respondent might say that the
household is female headed because the mother is present but say male headed if the father is
present; it is also unknown to what extent women might report themselves as household head
when in fact they are have little decision making power; and they may report their husband as
head when in fact he has little influence on daily decision making. The same is true for
subjective reporting from men. In short, if we base Household Headship on the subjective
response of the person interviewed we have no idea what 'female headed' or 'male headed' really
means. Thus we modified the category to be de facto household heads. Specifically, households
that respondents defined as male or female headed but in which the head resided with a live-in
spouse of the opposite sex we placed in the category of Male-Female Headed Household
(MFHH). The other two categories were Single Female Headed Households (SFHH) and Single
Male Headed Households (SMHH).
However, there were very few Single Male Chart 6.1: Household Type
Headed Households (177 or 11% of all Single
households: See Chart 6.1 right); and they Male Single
Headed Female
had much fewer members on average (Chart Headed
6.2). Part of the reason is that 38 (23%) of the Hshld,
11% Man and HsHld,
households had only a single male living in Woman, 27%
them; another 37 (22%) had only 2 people 62%
living in them; fully 82 (46%) of the men who
headed them had no children and 68 (38%)
were not and never had never been in union
(Table 6.1).
Table 6.1: Residents per Gender
Household Headship Type Chart 6.2: People per Hshld by Hshld Type
Number Male Single Single 6.0 5.3 5.1
of & Female Male
residents Female Hshld Hshld 5.0
1 2% 4% 23% 4.0 3.6
2 9% 11% 22%
3.0
3 17% 19% 17%
4 20% 21% 13% 2.0
Male & Female Single Female Hshld Single Male Hshld
5 19% 18% 7%
6 13% 13% 12%
7+ 19% 15% 6%
CARE Leogane & Carrefour Gender Survey 20
Thus, almost half of the Single Male-Headed households were not functioning units around
which productive labor was organized and children being raised; rather most were domiciles for
young men in transition from being children to becoming adults. Women on the other hand
almost never live alone and were members of larger households. This trend suggests that a
natural definition of household in the communities includes a lone or single female head or a
man and a female de facto co-head, whether she is identified as a household head or not. Thus,
the analysis below focuses on differences between Single Female-Headed Households and Male-
Female Headed Households. In the Charts and Tables we include data for Single Male Headed
Households but only for interest, not as a principal comparative category. In later sections we
will drop the Household Head categories entirely for the more useful categorization strategy,
"Sex of 1st and 2nd Most Important Contributors of Income."
Table 6.2: Population Household
Average of Average Number Average of
Household Type Household Pop of Servants Restavec
Single Male 3.79 0.05 0.29
Single Female 5.31 0.15 0.31
Man and Woman 5.68 0.06 0.41
Total 5.38 0.08 0.37
Urban vs. Rural Household Dimension
To add the dimension of urban vs. rural households, we consider the division of Carrefour
(entirely urban and peri-urban) vs. Leogane (peri-urban and rural), and we used this distinction in
the analysis of material household status on the following pages (Tables 6.3).
Chart 6.3: Household Types Carrefour vs. Leogane
80% 67%
62%
58%
60%
Male & Female
40% 29%
24% 27% Single Female Hshld
20% 13% 11% Single Male Hshld
9%
0%
Carrefour Leogane Total
CARE Leogane & Carrefour Gender Survey 21
Household Headship and Material Status Indicators
Tables 6.3 thru to 6.11 suggest unexpected differences between Single Female Headed
Households (SFHH) vs. Male and Female Headed Households (MFHH). Based on observations
seen in the Review of the Literature we expected that rural Single Female Headed Households
would be relatively well-off compared to their Male-Female headed counterparts and that urban
Single Female Headed Households would be economically worse off. What we found suggests
the opposite. Specifically, compared to Male-Female Headed Households, Single Female
Headed Households in Carrefour (entirely urban or peri-urban) more often have a concrete roof
(57% to 53%), more often have a flush toilet (20% to 17%), more often have a cistern or spigot
in the house or yard (34% to 25%), more often purchase bottled water (16% to 15%), more often
use propane gas to cook (7% to 5%), more often have electricity (98% to 97%), and more often
own both the home and the house that it is built on (52% vs. 49%). In addition to all this, Single
Female Headed Households in Carrefour spend more money on the oldest child's education
(US$30.24 vs US$25.04 per month).
In summary, with respect to every material variable measured, Single Female-Headed
Households in the more urban commune of Carrefour came out better off than those households
in which there is both a male and female head. While most of these differentials are not, for the
size of the survey, statistically significant, together they provide a strong suggestion that Single
Female-Headed Households in urban and peri-urban Carrefour are better off than their Male-
Female Headed Households counterparts (Tables 6.3 thru 6.11).
With respect to peri-urban and rural Leogane, Single Female Headed Households do not make as
strong a showing, but rather appear to be equal to Male-Female Headed Households. An equal
proportion of each has a concrete roof (6% to 6%), a flush toilet (5% to 5%), and uses propane
gas as cooking fuel (2% to 2%). Male-Female Headed households in Leogane more often have a
cistern or spigot in the house or yard (11% to 9%) and are more often hooked up to the national
electric grid (64% to 58%). But Single Female Headed Households more often purchase bottled
water (16% to 14%), they spend more on the oldest child's education (US$27.62 vs. US$25.03),
and they more frequently own both the home and land (77% vs. 72%; see Chart 6.4 & Tables 6.3
thru 6.11).
Table 6.3: Roof Type
Male & Single Female Single Male
Commune Type Female Hshld Hshld Total
Concrete 53% 57% 51% 54%
Carrefour Tin 41% 37% 45% 41%
Tarp 6% 6% 4% 6%
Concrete 6% 6% 7% 6%
Leogane Tin 86% 85% 85% 86%
Tarp 7% 8% 8% 8%
CARE Leogane & Carrefour Gender Survey 22
Table 6.4: Latrine
Single
Male & Female Single Male
Commune Type of Toilet Female Hshld Hshld Total
Flush Toilet 17% 20% 16% 18%
Block Latrine 59% 59% 66% 60%
Carrefour Wood Latrine 17% 17% 10% 16%
Hole 4% 1% 4% 3%
None 3% 3% 4% 3%
Flush Toilet 5% 5% 6% 5%
Block Latrine 44% 38% 51% 43%
Leogane Wood Latrine 30% 32% 27% 30%
Hole 11% 14% 7% 11%
None 10% 11% 9% 10%
Table 6.5: Water Source
Single
Male & Female Single Male
Commune Source Female Hshld Hshld Total
Cistern/Spigot at house 25% 34% 21% 27%
Cistern/Spigot not at house 71% 63% 75% 69%
Carrefour Spring 2% 1% 4% 2%
River 1% 1% 0% 1%
Other 0% 0% 1% 0%
Cistern/Spigot at house 11% 9% 8% 10%
Cistern/Spigot not at house 61% 67% 53% 62%
Leogane Spring 17% 16% 26% 17%
River 8% 4% 10% 7%
Other 3% 4% 3% 3%
able 6.6: Potable Water
Male & Single Female Single Male
Commune Type Female Hshld Hshld Total
Bottled 44% 46% 42% 44%
Carrefour Self-Treated 53% 52% 56% 53%
Untreated 3% 2% 3% 3%
Bottled 14% 16% 21% 15%
Leogane Self-Treated 64% 72% 43% 64%
Untreated 22% 12% 36% 21%
CARE Leogane & Carrefour Gender Survey 23
Table 6.7: Cooking Fuel
Male & Single Female Single Male
Female Hshld Hshld Total
Propane 5% 7% 5% 5%
Carrefour Charcoal 93% 91% 93% 92%
Wood 2% 3% 2% 3%
Propane 2% 2% 0% 2%
Leogane Charcoal 42% 51% 32% 43%
Wood 56% 48% 68% 55%
Table 6.8: Energy
Male & Single Female Single Male
Commune Sources Female Hshld Hshld Total
Grid 97% 98% 94% 97%
Generator 1% 1% 2% 1%
Carrefour Invertor 1% 0% 3% 1%
Solar Panel 0% 0% 0% 0%
Other 0% 0% 1% 1%
Grid 64% 58% 57% 62%
Generator 5% 3% 0% 4%
Leogane Invertor 9% 8% 11% 9%
Solar Panel 4% 7% 4% 5%
Other 17% 23% 29% 20%
Table 6.9: Monthly Educational Expenditure for Oldest Child
Male & Single Female Single Male
Commune Female Hshld Hshld Total
Carrefour $25.04 $30.24 $28.24 $20.02
Leogane $25.03 $27.62 $17.81 $18.26
Chart 6.4: Home Ownership
Own
Neither Table 6.10: Average
Own Home
and Land, 26% Cost of Rent (USD)
62%
Own Home House $327.49
Only, 12% Land $102.28
CARE Leogane & Carrefour Gender Survey 24
Table 6.11: Home Ownership
Male & Single Female Single Male
Commune Ownership Female Hshld Hshld Total
Own Home Only 10% 7% 9% 9%
Own Land Only 1% 0% 0% 0%
Carrefour
Own Both 49% 52% 55% 50%
Own Neither 40% 41% 36% 40%
Own Home Only 16% 11% 18% 15%
Own Land Only 0% 1% 0% 0%
Leogane
Own Both 72% 77% 65% 73%
Own Neither 12% 10% 17% 12%
Headship and Economic Contributions
In planning for the survey with CARE staff, we hypothesized that a tool more powerful than
headship in illuminating the causes underlying gender differential treatment and behavior would
be the extent to which women supported the economic wellbeing of the households. It is also
necessary to have such a measure when assessing male-female relationships within households
because, as seen with household type, in 27% of households there is no male-head, not even as
co-head. In short, we cannot effectively evaluate adult gender relations for cases where only one
gender is present (a woman).
Charts 6.5 thru 6.7, below, give an overview of the frequency of 1st and 2nd contributors by sex
of the contributors. In 70% of all households at least one of the two principal breadwinners is
female; for males, in 79% of households at least one male is a 1st or 2nd ranked financial
contributor. In only 19% of households are both primary breadwinners male and in only 13%
are both female. In 35% of households the primary breadwinner is male and the secondary is
female; and in 13% of cases it is the reverse, the primary breadwinner is female and the second
breadwinner male.
Table 6.12 and 6.13 list the different occupations by order of frequency (how many contributors
depend on that occupation for income) and by order of importance (whether it is the source for
first or second income contributors). Note in the tables the outstanding importance of commerce,
cited twice as often as the next nearest source of income, 81% of the practitioners of which are
women.
CARE Leogane & Carrefour Gender Survey 25
Chart 6.5: Female Breadwinners
80% 70%
60%
35% 30%
40%
20% 8% 13% 13%
0%
One Both 1st 1st Breadwiner At least one Neither of
Breadwinner Breadwinners Breadwinner Male, 2nd Breadwinner principal 2
Female, Other Female Female, 2nd Female Female breadwinners
Unknown Male female
Chart 6.6: Male Breadwinners
100% 79%
80%
60%
35%
40% 19% 21%
11% 13%
20%
0%
One Both Both 1st Breadwiner 1st At least one Neither of
Breadwinner Breadwinners Male, 2nd Breadwinner Breadwinner principal 2
Male, Other Male Female Female, 2nd Male breadwinners
Unknown Male Male
Chart 6.7: Comparison of Proportion of Sample by Gender
of 1st and 2nd Breadwinners: Male vs. Female
100% 79%
80% 70%
60%
35% 35% 30%
40% 21%
8% 11% 13% 19% 13% 13%
20%
0%
Female/Male, Both 1st 1st At least One Neither
Unknown Female/Male Female/Male, Male/Female, Female/Male Female/Male
2nd 2nd
Male/Female Female/Male
CARE Leogane & Carrefour Gender Survey 26
Table 6.12: Source of 1st and 2nd Contributor Income by Sex of
Contributor
1st Contributor 2nd Contributor
Occupation Female Male Female Male Total
Tailor 2 3 1 1 7
Rental property 2 2 2 1 7
Loaning money 2 2 4 1 9
Workshop 2 8 0 0 10
Restaurant 7 2 5 2 16
Labor 1 13 1 7 22
Store 4 6 12 1 23
Manual labor 0 15 3 11 29
Artisan 1 15 3 11 30
Remittances 14 10 9 7 40
Taxi 2 67 5 46 120
Other 24 95 48 51 218
Skilled labor 0 175 3 78 256
Farming 6 196 28 98 328
Paid employment 61 256 71 132 520
Commerce 402 147 567 75 1191
Total 530 1012 762 522 2826
Table 6.13: Total Sources of Income First and Second Income
First Source Income Second Source of Income
Tailor Business 0.3% Tailor Business 0.2%
Loaning money 0.2% Loaning money 0.2%
Rental property 0.3% Rental property 0.3%
Restaurant 0.6% Restaurant 0.7%
Store 0.6% Store 0.8%
Workshop 0.6% Workshop 0.8%
Labor 0.9% Labor 0.9%
Artisan 1.0% Artisan 1.0%
Manual labor 1.0% Manual labor 1.0%
Remittances 1.7% Remittances 1.3%
Taxi 4.5% Taxi 3.3%
Skilled labor 10.9% Skilled labor 5.4%
Farming 12.6% Farming 8.0%
Paid employment 20.5% Paid employment 13.9%
Commerce 34.3% Commerce 40.8%
Other 10.0% Other 21.2%
CARE Leogane & Carrefour Gender Survey 27
Table 6.14: Sex of First and Second Income Providers
by Sex of Respondent Identified Household Head
Self-Identified Female & Female & Female Male & Male &
HsHld Head Unknown Unknown Female & Male Male Female Male
Female 7% 19% 33% 16% 5% 14% 7%
Male 4% 1% 2% 6% 15% 38% 34%
Male & Female 2% 4% 3% 17% 12% 50% 11%
All households 4% 8% 12% 13% 11% 34% 18%
Differential Impact of Women vs. Men Being in Control of Household Resources
The intuitively obvious utility of having a measure of female economic power is that we can
explore the extent to which female vs male control over household resources determines factors
such as,
1) the nutritional well-being of other household members, particularly children, as
manifest in food expenditures
2) gender specific performance of household chores,
4) how women are treated, or mistreated, by their husband and others around them.
Household Expenditures on Food
In the literature regarding the role of women in development a common assumption is that the
more women are in control of household finances the greater the proportion of the household
budget gets spent on nutrition (World Bank 2002). In preparing for the survey we made the
same assumption and we included questions to test the veracity of this expectation. As seen
below, the data at first seemed to support the notion that women spend more on household
nutrition. But upon closer inspection the evidence suggests that men, when in control of the
household budget, may spend as much or more on nutrition than do women.
Expenditures on Food by Household Headship Type
The first issue we look at is expenditures on food per household per household type (Chart 6.8).
But because of the different size of households per type, once again seen in Chart 6.9, it is more
useful to examine expenditures per person for the different house types, as seen in Chart 6.10. In
Chart 6.11 we see that when we consider household size, or rather expenditures per person per
household type, Single Male Headed Households are seen to spend more on food than both
Single Female Headed Households and Male-Female Headed Households. This is probably a
consequence of something other than consideration for household members; specifically an
economy of scale, the larger households preparing more food at a more economic price. Thus,
we are left once again with the image of Single Female Households operating more favorably
than their Male-Female Headed Households counterparts. Chart 6.12 illustrates that the
relationships is not, for the sample size, statistically significant. Nevertheless, based on the more
favorable resources, infrastructure and wealth of Single Female Headed Households seen in the
previous section, we can infer that Single Female Headed Households once again have more
resources or are at least able to more effectively marshal greater resources than Male-Female
Headed Households.
CARE Leogane & Carrefour Gender Survey 28
Chart 6.8: Daily Food Expenditures (USD) Chart 6.9: People per Hshld by Hshld
by Gender House Type Type
$11.00 $9.94 $10.26
6.0 5.3 5.1
$10.00
$8.47 5.0
$9.00 3.6
4.0
$8.00
3.0
$7.00
2.0
Male & Female Single Female Single Male
Male & Female Single Female Single Male
Hshld Hshld
Hshld Hshld
Chart 6.10: Per Person Daily Food Chart 6.11: Statistical Significance of
Expenditures (USD) by House Type Household Type by Average Food
Expenditures (p<.05)
Male &
Female
Expenditures on Food by Household Head and Income Contributors
We next examine the influence of the new typology 'sex of first and second income contributors.'
In Table 6.12 we see that those households where women are primary contributors of income
spend more money on food than other households. But as seen in the following sections on who
controls the household budget, this does not necessarily mean that women are more inclined than
men to spend money on family nutrition.
Chart 6.12: Average Daily Food Expenditures (USD)
by Gender of Principal 2 Breadwinners
$15.00 $10.40 $11.36
$9.02 $9.87 $10.88 $9.84
$10.00 $8.50 $8.18
$5.00
$0.00
Unknown Female Female, Female, Male Male, Male, Male All
Female Male Female Categories
CARE Leogane & Carrefour Gender Survey 29
Male vs. Female Control Over the Household Budget
Women in Haiti are traditionally the custodians of the household budget, we know this from the
ethnographic literature (Murray 1977; Smucker 1983; Lowenthal 1987; Schwartz 2000). Only in
the case of Single Male-Headed Households--that, as seen, have few resident women and for the
most part do not classify as functioning household--do women control the budget in less than
50% of cases. Overall, in 71% of all households it is a woman who controls the budget (Chart
6.13 & 6.14). The upshot is that when present, women are overwhelmingly the custodians of the
budget; and the more women contribute the more pronounced is the relationship.
Chart 6.13: Woman Manages Household Budget
by Household Type
All Households 71%
Single Female Hshld 91%
Male & Female 71%
Single Male Hshld 16%
0% 20% 40% 60% 80% 100%
Chart 6.14: Female Manager of Budget by
Gender of 1st and 2nd Contributors of Income
All Households 71%
Male 1st & Male 2nd 31%
Male 1st & Unknown 2nd 53%
Male 1st & Female 2nd 75%
Female 1st & Male 2nd 86%
Female 1st & Female 2nd 97%
Female 1st & Unknown 2nd 97%
Unknown 88%
0% 20% 40% 60% 80% 100% 120%
CARE Leogane & Carrefour Gender Survey 30
Female Control of the Budget and Household Expenditures on Food
Despite the fact that we have seen that Single Female Headed Households tend to spend more on
food than Male-Female Headed Households, when we examine expenditures in lieu of who
controls the budget it appears that males in our sample spend more on food (Chart 6.15 & 6.16).
Chart 6.15: Gender of Who Controls the Budget
by Per Person Expenditures
$3.50
$3.00 $1.94
$2.50 $1.75
$2.00
$1.50
$1.00
Female Male
Missing =235
Chart 6.16: Food Expenditures Per household by
Gender of Who Controls Budget
$11.00
$10.50 $10.30
$9.93
$10.00
$9.50
$9.00
$8.50
$8.00
Female Male
One possible critique of the finding is lower presence of adult females in these household and the
fact, seen earlier, that Single Male Headed households are much smaller than those with women
co-heads or those with no man at all. But as seen in Chart 6.17, even if we reduce the correlation
to expenditures per person and isolate in the analysis Household types we still find that males
who control the budget tend to spend more than females. The relationship is not, for the sample
size, statistically significant--as seen in the Chart 6.17. Moreover, it may still be true that women
in control of the budget better feed the household by virtue of their role as marketers and access
to better prices and trading partners. Nevertheless, the observation casts doubt on the assumption
that Haitian women are more inclined to spend money on food for the household than their male
counterparts.
CARE Leogane & Carrefour Gender Survey 31
Chart 6.17: Comparison of Per Person Hshld Food
Expenditures by Gender that Controls Budget and
$3.50 Single Male HdHshld (p < .05)
$3.00
$2.50
$2.40
$2.00 $1.90 $2.00 $1.95
$1.81
$1.50
$1.00
$0.50
$0.00
Female Controls Male Controls Single Male Not Family of All Households
Budget Budget Headed Respondent
Chores
Another area of analytic interest is the impact of female economic status within the household on
who is performing chores. In Table 6.15 we see that adult women and girls assume the bulk of
the responsibility for household labor.
Table 6.15: Who is the Primary Performer of Household Tasks by Sex and Age
Man and All No
Women Everyone Woman Men Girls Boys Children One
Fetches Water 25% 27% 7% 12% 11% 8% 6% 2%
Washes Clothes 57% 13% 6% 6% 10% 2% 2% 0%
Washes Dishes 47% 12% 5% 5% 21% 2% 4% 0%
Child Care 28% 14% 10% 3% 4% 1% 1% 32%
Takes Children to School 16% 5% 6% 6% 2% 2% 0% 50%
Store Purchases 36% 24% 16% 6% 6% 4% 3% 2%
Cleans House 55% 12% 6% 5% 14% 2% 3% 0%
Plans Meals 58% 5% 19% 12% 2% 1% 0% 1%
Works Outside Home 33% 4% 30% 18% 1% 2% 0% 10%
Market Purchases 26% 15% 15% 8% 4% 3% 1% 22%
Makes Meals 63% 11% 6% 5% 9% 1% 1% 0%
CARE Leogane & Carrefour Gender Survey 32
Female Economic Contributions and Male Participation in Domestic Chores
In Chart 6.18 we use the single chore of "washing dishes" to evaluate the impact that female
financial contributions have on the probability that males will participate. What we find is a clear
and direct relationship between male contributions to washing dishes and the economic power of
women: the more women contribute the more males help wash dishes; the less women contribute
the less likely males are to participate in dish washing. The relationship is especially noteworthy
as it stands out even without controlling for the fact that households with only female income
contributors have fewer males present to wash dishes while households with only male
contributors have fewer females.
Chart 6.18: Females Only Wash Dishes
by Gender of 1st and 2nd Income Contributors
(Single Male Headed Hshlds Excluded)
100.0%
90.0%
77.2% 78.7%
80.0%
69.8%
70.0% 66.5%
64.3%
60.0%
50.0%
41.4%
40.0%
CARE Leogane & Carrefour Gender Survey 33
Male Control Over Women
When preparing the survey, we wanted to
know to what degree men directly control Table 6.16: Who Has Final Say
the behavior of women in terms of decision Sleeps in
making, geographic mobility and Person with the Big
participation in community action and Final Say House Decisions
development activities. We assumed that
Woman 19% 24%
male repression would be manifest in their
own and other opinions of who makes Man 33% 27%
major household decisions, who wins Man & Woman 37% 42%
arguments, if and who has to ask Other 11% 7%
permission of whom to travel or join an
organization. In Table 6.16 we see that men
do tend to prevail in making major decisions and have the final word on who sleeps in the house.
But for other responses we once again--despite knowing that woman are relatively prominent in
the domestic sphere--got a surprise.
Whether the respondent was a male or female, they reported that the woman tends to win
arguments with her partner more often than the man (Chart 6.19 & 6.20). When we examine the
relationship in light of first and second financial contributors to the household (6.21) we find a
clear relationship between whether a woman is an argument winner and the place of women in
the household as economic contributors. In households where both 1st and 2nd contributor is a
woman, females are three times more likely to be reported the usual argument winners: in 61%
of cases the woman was reported as the usual winner and in 19% of cases the man was the usual
winner. In contrast, when 1st and 2nd contributors are men, women are less likely to be the
argument winner by a ratio of 3 to 2: in 47% of the cases the man is usually the winner and in
33% of cases the women was reported as the usual winner. Note however, that while the trend
was clearly associated with female economic status, in every category except those where both
economic contributors are male the woman was more often the usual winner. Compromise was
approximately equal response for all the categories.
Chart 6.19: Who Usually Wins Chart 6.20: Who Usually Wins
Arguments by Sex Arguments Between Partners
Respondents (for all respondents with
Female (n=602) Male (n=650) partners; n = 1,252)
60% 50%
42%
50% 38%
50% 44% 40%
40% 34%
31% 30%
30% 22% 20%
18% 20%
20%
10% 10%
0% 0%
Compromise Male Wins Female Wins
CARE Leogane & Carrefour Gender Survey 34
Chart 6.21: Winner of Arguments
70% with partner by Sex and 1st & 2nd Income Contributors
61%
60%
45% 47% 47% Winner
50% 41% 44% 41%
37% Compromise
40% 34%
32% 33%
30% Woman
19%
20% Male
10%
0%
Female Female & Female Male Male & Male Male
Female Unknown Male Female Unknown
Chi Sq p < .000
Women also appear to be less under the control of their spouse than vice versa. Women reported
asking permission to travel or to join an organization less frequently than men (Chart 6.22 &
6.23); women, rather than men, are more often the person who is being asked permission (Tables
6.17, 6.18, & 6.18); and even when respondents are told "no"-- that they cannot travel or join an
organization--women reported being more likely to do so anyway (Charts 6.24. & 6.25). In
summary, we found that males not only control or repress women less than we expected, women
appear to do most of the controlling, of both sexes. vii
Chart 6.22: Must Ask Permission to Chart 6.23: Must Ask Permission to
Visit Family Far-Away by Sex of Join an Organization
Respondent 72% 70%
80%
80% 68%
78%
64%
64%
75% 60%
Female (n=820) Male (n=823) Female (n=820) Male (n=823)
CARE Leogane & Carrefour Gender Survey 35
Table 6.17: Needs to Ask Permission to Visit Table 6.18: Needs to Ask Permission to Join
Faraway by Sex Organization by Sex
Permission Seeker Permission Seeker
Female Male Both Sexes Permission Female Male Total
Permission
Giver (n=692) (n=759) (n=1,451) Giver (n=582) (n=559) (n=1,241)
Male (n=620) 70% 18% 43% Male (n=526) 72% 16% 42%
Female (n=831) 30% 82% 57% Female (n=715) 28% 84% 58%
Table 6.19: Who asks permission of Who
(more than one possible response; n = 1513, missing = 2)
Visit Family Far Way Join an Organization
Female Male Total Female Male Total
Permission Giver (n=693) (n=798) 1,495 (n=693) (n=798) 1,495
Grandfather 0 1 1 1 1 2
Grandmother 2 4 6 2 4 6
Uncle 4 5 9 4 2 6
Not Family 3 7 10 3 3 6
Unspec, Family 13 12 25 8 9 17
Cousin 7 20 27 6 18 24
Aunt 16 20 36 10 17 27
Sister 26 26 52 15 29 44
Brother 17 39 56 24 34 58
Daughter 58 27 85 49 29 78
Son 56 30 86 56 23 79
Father 43 60 103 36 45 81
Mother 105 162 267 85 122 207
Husband 365 - 365 300 - 300
Wife - 385 385 - 353 353
Chart 6.24: Sex of Those Who Chart 6.25: Sex of Those Who
Would Visit Even if Told "No" Would Join Even if Told "No"
12% Female (n=640) Female (n=526)
10% 13%
14% Male (n=580)
10% Male (n=662)
12%
8% 7% 10%
6% 8% 6%
6%
4%
4%
2% 2%
0% 0%
CARE Leogane & Carrefour Gender Survey 36
Violation of Female Property and Ownership
To get an idea of the extent to which women are denied autonomous control over property we
asked the men and women sampled if, since the earthquake, anyone had taken or sold the
respondent's belongings without being asked. The objective was to measure the extent to which
other family members, particularly male spouses, respect--or disrespect-- female economic
autonomy. We left the question open, meaning we asked not just if family or a husband took
their belongings without permission, but if anyone had taken their belongings. We also asked
the same question of men. As can be seen in Chart 6.26 and Table 6.20, what we found was that
women do suffer more property violations than men; but it was not family who was taking their
goods. It was non family We did not ask specifically about the identity of non-family, but the
greater losses that women suffer is likely a reflection of female involvement in itinerant
marketing and their consequent exposure to petty thievery on buses and in markets If in looking
at Tablet 6.20 we only consider losses to family, men report suffering almost three times as many
losses as women: 43 for men to 17 for women. Perhaps most interesting of all, however, is that
in the three year wake of one of the greatest disasters in human history, a time when we have
been told that wanton crime has swept through Port-au-Prince (Kolbe et. al. 2010; Kolbe and
Muggah 2012; Numbeo 2013), only 20% of our 1,643 respondents reported anything at all being
taken from them. Similarly, out of 820 female respondents and 823 male, only one woman and
one man reported that a spouse had taken anything belonging to them without their consent.
Chart 6.26: Respondents who have Table 6.20: Respondents who report
had Goods Taken Since the that Someone Took Something from
Earthquake them Since Earthquake
Person Who
25% 23%
Took Female Male Both
20% 17% Not Family 169 100 269
15% Relative unlisted 15 35 50
10% Cousin 1 6 7
Brother 0 1 1
5%
Husband 1 0 1
0% Wife 0 1 1
Female (n=820) Male (n=823)
Grand Total 820 823 1643
Female Dependency on Men
In this next to final section of Households we see that in the opinions of the men and women
sampled it is not women, but men who are more often thought of as the most materially
dependent on their spouse. When asked about material interdependency of spouses--meaning
dependency for survival and maintenance of the household's livelihood strategies and posed as
the question ,"who needs the other more, a husband needs his wife or a wife is in greater need of
her husband"--three fourths of all respondents said that men and women need one another
equally (Chart 6.27). But if we only consider those who said that either men or women were
CARE Leogane & Carrefour Gender Survey 37
more dependent, twice as many respondents said that men need women more than vice versa
(ibid). Moreover, when asked directly if they can live without having a spouse 51% of all women
vs. 12% of all men said yes (Chart 6.28). Put another way, 49% of women said they could not
manage without their husband, but 88% of men said they could not manage without their wife.
When we considered only those respondents who have been or currently are in union the figure
is 46% of women who said they can get by without their husband versus only 10% of men who
said they can get by without their wife (Chart 6.29). The relationship was independent of where
the person lived--urban, peri-urban or in the countryside--indicating there was little difference
between declared independence of the respondent and the degree of urbanization in the area
where he or she lived (Table 6.21). Thus, in the aggregate men in the studied communities
overwhelmingly believe they need their spouse, whether the wife has income or not; on the other
hand, about half of women view themselves as able to survive without their husband. The
women explained their independence (Table 6.22) in terms of their own financial resources
(67%) and support from their children (24%).
90% 85%
6.27: Which Spouse Needs
77%
80% the Other More:
69%
70% Man or Woman
60%
50%
Female (n=820)
40%
30% 21% Male (n=823)
20% 16%
11% 10% 7%
10% 4% Men and Women
0% (n=1.643)
Men Need Women They Both Need Women Need Men
More Each Other Equally More
Chart 6.28: "Yes" Can "Live"
Without a Spouse
60% 51%
(all respondents)
50%
40%
30%
20% 12%
10%
0%
Female (n=820) Male (n=823)
All Respondents
CARE Leogane & Carrefour Gender Survey 38
Chart 6.29: "Yes" Can Live Without Having a Spouse
For Respondents in Union
50% 46%
40%
30%
20%
10%
10%
0%
Female (n=498) Male (n=470)
Respondents in Union
Table 6.21: Count of Respondents
Who Can Live Without Spouse by Location
Location Sex Yes
Female 45%
City
Male 9%
Female 44%
Countryside
Male 9%
Female 49%
Peri-Urban
Male 13%
Table 6.22: Reasons Respondents can Live Without Spouse
Has Own Has Children To
Resources Lean On Other
Female (n=230) 67% 24% 9%
Male (n=49) 86% 14% 0%
Both (279) 70% 23% 7%
Who Works the Hardest
A final point we found in the surveys in interpreting the differential dependency of men and
women and contributions to the household has to do with the way respondents view the work
efforts of men vs. women. The conspicuous role of women in domestic labor and frequent sight
of women walking with burdens on their heads leads many observers to assume that popular
class Haitian women work harder than men and, by corollary that, that men are not working as
hard--another contributing element to the international image of Haitian women as repressed
(e.g. Bell 2001).
CARE Leogane & Carrefour Gender Survey 39
And it may be true that the women are working
Chart 6.32: Sex of All People
harder. But respondents in Carrefour and
Leogane did not report seeing the situation in Respondents Identified as
this way. In Table 6.22 and Charts 6.32 thru Working the Hardest
6.34 we see that no matter who is the
Female,
respondent, male or female, and no matter if 35%
talking about him or herself, someone else, or if Male ,
we only consider those respondents who 65%
identify someone else in the house as the
hardest working member of the household, a
consistent 63%-77% of those people who are
seen as the hardest working in the household are (n =1,567; non-family and "other" = 76)
male; 33% to 37% are female.
Chart 6.33: Sex of Respondents Self
Identifying as Working the Hardest
Table 6.23: Who Respondents Say
Works Hardest
Person Number Percent
Female,
Grandfather 1 0% Male, 36%
Grandmother 5 0% 64%
Uncle 19 1%
Aunt 24 1%
Sister 24 1%
Cousin 25 2% n=855
Daughter 26 2%
Son 32 2%
Brother 44 3%
Chart 6.34: Sex of Other People
Wife 48 3%
0, 0% Respondents Identified as Working the
Other 51 3%
Hardest
Father 89 5%
Mother 109 7% Female,
Husband 291 18% 33%
Respondent 855 52% Male, 67%
Grand Total 1,643 100%
n=712
CARE Leogane & Carrefour Gender Survey 40
Conclusion
I in the Review of the Literature it was seen that researchers have long noted the prominent role
of women in the Haitian economy. Anthropologists doing longitudinal ethnographic research
report that women overwhelmingly control local retail marketing; and tantamount to a cultural
rule in Haiti is that the household is the domain of women. We also saw that at least one study
found that in rural areas Female Headed Households are four times less likely to be "extremely
poor" than are Male Head Households. In this first section of the analysis we have seen that
similar patterns prevail in Leogane and Carrefour. We found that rural Single Female-Headed
Households were materially on par Male-Female Headed Households; but somewhat
surprisingly, we also found that urban and peri-urban Single Female-Headed Households in our
samples were materially as well, or better, off than households where both a male and female
head is present. We also found that in many households women are among the primary financial
contributors and, even when not, women are usually in control of household budgets.
With respect to repression of females, we saw in the Review of the Literature that the EMMUS
report women prevailing in most household decision making processes, exercising a large degree
of control over their own income and the family budget, and being the primary disciplinarians of
children. What we did not get from the EMMUS and other studies, and we do get to at least
some degree from the present study, is information on the degree to which men are not part of
the decision making process and must answer to women. What we found is that men more often
lose arguments to their spouse, they more often feel the need to ask permission to travel or join
an organization and, if told no, they are less likely than women to disobey. We also found that
household members, including males, more often defer to women for permission to travel or join
an organization.
In short, men in our samples appear more submissive to their wives than vice versa. Moreover,
both male and female respondents more frequently thought that men were more in need of their
spouse than vice versa and when asked if they could manage without their spouse men were far
more likely to say no. Despite male dependency on their wives and the prominent role of women
and girls as carrying the greater burden in performing domestic chores, both men and women
more often reported a male as the hardest working members of the household.
The significance of these findings in making aid more effective is that many organizations,
including CARE, made Female Headship a criterion for receiving aid in post-earthquake
Haiti. The assumption is that female-headed households rather than male, or joint male-
female headed households, a) depend on income from women who have fewer
opportunities than men and hence and b) are in greater material and nutritional need. But,
what we saw in this section is that when we speak of "female headed households" in Léogâne
and Carrefour, there arguably may be no other type of household. Moreover, in understanding
the prominence of "Single Female Headed Households," it helps to note that the image that often
springs to mind is of a desperate single young mother with children. But many female household
heads in the Carrefour and Léogâne samples may better be described as middle aged matriarchs
orchestrating the work activities of older children, receiving money from them and from multiple
other sources; women who are as capable of earning their own money via marketing as many of
the men around them; and certainly more important than the men in terms of managing the
household and the people who live in it.
CARE Leogane & Carrefour Gender Survey 41
7. Gender and Violence
As seen in the Review of the Literature, Haiti has been presented as one of the most female
repressive countries on the planet. The point is especially poignant since the 2010 earthquake.
Grass roots NGOs, human rights organizations, and the international press have reported
physical and sexual violence against popular class Haitian women in excess of that reported for
the Western Congo, site of what can only be called a current rape holocaust. In the surveys we
attempted to clarify these issues.
Regarding domestic violence, in lieu of the prominent role that women play in the domestic and
local economy there is good reason to question the portrayal of Haitian women as extremely
repressed. Intuitively, we can expect popular class Haitian women to be aggressive in defending
their commercial interests and domestic status. We saw in the literature review that some
anthropologists have in fact report them to as or more violent than their spouses. Moreover, our
understanding of gender based violence in Haiti is skewed by inherent bias in at least some of the
major surveys on gender. For example, the Haiti Demographic and Health Surveys (EMMUS)
make no mention of female aggression toward men; men are not asked if they have been subject
to assault from their wives; nor are women asked about their own participation in violence. The
effect, whether intended or not, is to present women as passive victims.
Regarding, extra-domestic violence against women, since the 1991-1994 military junta, through
the 2004 coup, and up to the 2010 earthquake, there have been reports from activists, human
rights organizations, and scholars of epidemic levels of extra-domestic rape (Kolbe et. al 2010,
Amnesty International 2011). The claims have been widely repeated in the international media
(Miami Herald 2004; NYT 2007; AP 2010; Huffington Post 2010; CNN 2012). Following the
2010 earthquake reports of epidemic rape intensified and many of the NGO programs since that
time have focused specifically on addressing the issue----including CAREs work in Leogane and
Carrefour.
To clarify issues associated with domestic and extra-domestic violence, we included in the
Leogane and Carrefour surveys questions regarding which sex respondents believe are most at
fault for domestic violence, about physical violence at the hands of family and partners and in
the analysis we examine the probability of occurrence of domestic violence in lieu economic
indicators. To clarify the issue of rape and extra-domestic violence against women we asked
respondents how many people they knew who had been raped since the 2010 earthquake, and
then drawing on that information we used the technique known as "scaling up" to gain an
approximate estimate of the incidence of rape. We also asked questions regarding informants
views on security and about knowledge of recourse to services for victims and laws meant to
protect women from violent assault.
CARE Leogane & Carrefour Gender Survey 42
Respondent Views on Gender and
Cause of Domestic Violence Chart 7.1: Who Respondents Believe is most
We began by asking the general question often the Cause of Male Vilence Against
who is more often the cause of violence 80% Women 74%
against 'women, men or women?' 61% of
60% 51% 49%
respondents said women are more at
fault. When examined by sex of 40% 26%
respondent, men more often blamed
women; the figures were 74% of men 20%
who said women were more often blame 0%
vs. 26% of men who said it was more Men are more the cause Woman are more the
often the man's fault. Women were more cause
divided: 51% vs. 49% said that men were Female (n=820) Male (n=823)
more often the cause of violence against
women (Chart 7.1).
Frequency of Violence and Protagonist
To measure the extent to which both men and women suffer or participate in violence we asked
both males and females about violent attacks. The specific two questions we used to begin the
inquiry were, "when was the last time you were beaten?" followed by, "who was the person who
beat you?" We used this question because of the expediency of not having to document and
clarify multiple violent incidences per respondent, i.e. it was easier to simply ask about the last
violent incident. We formulated the question using the Creole word, bat, "beaten," which is the
word used in physically attacking and dominating another person. Note that unless the
punishment is very severe, children are considered to be whipped (kale). The reason we posed
the question in this way is to bias the respondents interest toward physical violence as an adult.
We were not specifically interested in child punishment. Nevertheless, because of relatively low
overall incidences of aggression we also include in the analysis the response "beaten as a child"--
indicating severe corporal punishment as a child.
What we found was that in every category except the past three years men suffer more from
violence than women (Table 7.1): men were more likely to be beaten as a child and more likely
to be beaten as an adult. Note however that 58% of women and 44% of men claim to never have
been beaten in their lives, even as a child. This is significantly less than reported in EMMUS
studies, and the reason is likely because the EMMUS consider any corporal punishment of
children, not the "bat"--beaten--seen above.
Table 7.1: Last Time Beaten by Sex of Respondent
Female Male Total
Last Time Beaten Number Percent Number Percent Number Percent
In the past 3 years 62 8% 43 5% 105 6%
Adult but 3 + Years Past 34 4% 72 9% 106 6%
When a Child 249 30% 345 42% 594 36%
Never 475 58% 363 44% 838 51%
CARE Leogane & Carrefour Gender Survey 43
Identity and Sex of Aggressors
When we looked at who was the aggressor in violent acts (Table 7.2 & Chart 7.2), we found that
43% are women vs. 48% that are men; in 9% of reported incidents the sex of the aggressor was
unknown, a side effect of not asking sex specific information for cousins and non-family. The
high number of women is a reflection of their prominent role in the household and as family
disciplinarian: 90% of the females identified aggressors were the respondent's mother or
grandmother (75% of male aggressors were Fathers).
Table 7.2: Person Who Beat Respondent the Last Time He/ She was Beaten
Who Got Beaten
Female Male Total
Who Did the Beating Number Percent Number
(n=400) Percent Number
(n=519) Percent
(n=918)
Mother or Gran 154 39% 200 39% 354 39%
Father 123 1% 208 40% 331 36%
Husband/Wife 65 17% 9 2% 74 8%
Teacher 12 3% 30 6% 42 5%
Brother 11 3% 12 2% 23 3%
Aunt 7 2% 10 2% 17 2%
Uncle 4 1% 12 2% 16 2%
Stranger 2 1% 13 3% 15 2%
Boyfriend/girlfriend 7 2% 2 0% 9 1%
Sister 5 1% 4 1% 9 1%
Son or Daughter 0 0% 1 0% 1 0%
Cousin 0 0% 5 1% 5 1%
Police 0 0% 5 1% 5 1%
Grandfather 0 0% 1 0% 1 0%
Other 6 2% 8 2% 14 2%
Chart 7.2: Sex of Violent Protagonists
(918 cases)
60%
48%
50% 43%
40%
30%
20%
9%
10%
0%
Female Male Unknown
CARE Leogane & Carrefour Gender Survey 44
Spousal Abuse/Violence Against Respondent
If we eliminate the categories for 'beaten as a child' and only consider the 223 reported cases of
respondents beaten as an adult, 65 (33%) of the known aggressors were women and 135 (67%)
were men (Table 7.3). Very significantly we see that 65 women were beaten by their husbands.
This means that of 572 women ever in union, 65 (or 11%) had been beaten by their husbands.
Not to be overlooked, of 539 men ever in union, 9 (or 2%) had been beaten by their wives.
Table 7.3: Person who Beat the Respondent for Adults and Last Three Years Only
Who Beat You as an Adult or within Female Male
Husband the Past 3 Years 65 0
Mother or Grandmother 10 29
Father 10 38
Stranger 1 10
Teacher 1 9
Wife 0 9
Other 0 6
Aunt 0 3
Grandmother 0 2
Police 0 5
Cousin 0 5
Uncle 0 3
Boyfriend/girlfriend 4 2
Brother 3 3
Sister 2 1
Son or Daughter 0 1
Grandfather 0 1
Total 96 127
Male Spouse Violence Against Female Respondent by Female Household Financial
Contributions
Chart 7.3 shows that, while not statistically significant given the sample size, there is
nevertheless a strong suggestion that a woman is more likely to have been beaten by her husband
if she is a primary or secondary contributor of household income. This seems at first to be
counterintuitive. When designing the questionnaire and in discussion with CARE staff, we
expected that the less a woman contributed financially to a household the more likely she would
be subjected to physical violence from her spouse. In view of our finding, an alternative
explanation may be that the more economically powerful a woman is the more likely she is to
enter into a violent conflict with her spouse. This may be because of aggression or resentment on
the part of her husband or it may be because the woman has more to defend, is more confident in
because of her high economic status, and hence is more likely herself to be an aggressor; or
perhaps better phrased, she is more likely to be a violent defendant or a combatant rather than a
passive victim.
CARE Leogane & Carrefour Gender Survey 45
Chart 7.3: Woman was Beaten by her Spouse by First
15%
and Second Contributors of Household Income
(p < .05)
10%
6.92%
5% 4.90% 5.74% 4.34%
2.82%
1.34%
0%
Female Female Female Male Male Male Male
Unknown Female Male Female Unknown
Spousal Violence (Against Respondent) and Degree of Urbanization
Similar to the counter intuitive finding that the more a woman contributes financially to the
household the more likely she is to have been beaten by her spouse, the data suggests, contrary to
expectations, that domestic violence in the city is less common than among rural couples.
However, the relationship is not, given the sample size, statistically significant (Charts 7.4 &
7.5).
Chart 7.4: Domesitic Violence by
Chart 7.5: Domestic Violence by
Urbanization (City, Countryside,
Urbanization (Countryside vs Peri-
Peri-Urban: p < .05)
25% Urban & City: p < .05)
25%
20%
16.9% 20%
15% 16.9%
12.1% 15%
10%
8.8% 10%
9.9%
5% 5%
0% 0%
City Countryside Peri-Urban Countryside Peri & City
Domestic Violence Against the Respondent vs. Socio-Economic Status
In Charts 7.6 thru 7.8 we also test the correlation between domestic violence and Socio-
Economic Status. In this case we included as proxy indicators of domestic violence the
categories of "Beaten as Adult by Spouse or Lover," "Beaten as Adult by Person Other than
Spouse or Lover," "Beaten as a Child," and "Never Beaten." As proxy measures of socio-
economic status we used ,"Amount Spent per Month on Tuition for Oldest Resident Child," as
well as "Roof" and "Latrine" types. Households where no money was spent on child's education
were omitted because of the confounding factor of no children in the household.
As seen in Chart 7.6 people beaten by spouse or lover and people beaten as children were more
likely to live in households where less money was spent on education than those people who had
never been beaten or who reported being last beaten by someone other than spouse or lover. The
relationship was statistically significant.
CARE Leogane & Carrefour Gender Survey 46
Chart 7.6: Mean Household Monthly Educational Expenditures
on Oldest Child by Aggressor in Last Incidence of Domestic
Violence
$23
$21
$20.28 $20.00
$19
$17 $17.80 $17.89
$15
As an adult by When a child by As an adult by non Never beaten
spouse or lover parent or other spouse
For Roof Type (Chart 7.7) we only tested the
relationship with "Beaten by Spouse or Lover." We Chart 7.7:
found that respondents living under a tarp were twice Beaten by Spouse or Lover by
as likely to have been beaten by a spouse or lover as Type of Roof
those living under a concrete roof. Those living under 16%
a tin roof were 35% more likely than those living 14%
under a concrete roof to have been beaten by a spouse 12%
or lover. Neither relationship was, given the sample 10%
size, statistically significant. This is arguably because 8.3%
8%
very few people in the sample (7%) lived under 6%
4.0% 5.4%
tarps. 4%
2%
For Latrine Type (Chart 7.8) we again tested all four 0%
formulated categories of domestic violence. The only Concrete Tin Tarp
relationship statistically significant is the rather
quizzical finding that people with only a "hole" or "no
latrine" were more likely to report never to have been beaten at all.viii
Chart 7.8: Type of Household Latrine by Last Incidence of
Domestic Violence
Flush Toilet Block Latrine Wood, hole or none
60% 56%
48%
50%
40% 40% 47%
40%
29%
30%
20%
7% 8% 9% 6% 6%
10% 4%
0%
As an adult by non When a child by As an adult by Never beaten
spouse parent or other spouse or lover
CARE Leogane & Carrefour Gender Survey 47
Reasons for Violence Against Respondent
In Table 7.4 it can be seen that when we consider all motivations for "beatings", the most
common are economic (24%) and then jealousy (19%). If we consider only motivation for
beatings as an adult (Table 7.5), the overwhelmingly most common motivation is jealousy (57%
of cases). Very interestingly, 71% of women and 88% of men said that they deserved their last
beating (Table 7.6 & 7.7).
Table 7.4: Why Beaten for All Cases
Respondents
Female Male Total
(n=345 cases) (n=460 cases) (n= 805 cases)
Response Number Percent Number Percent Number Percent
Argument Over Money 4 1% 7 2% 11 1%
Over a Lover 16 5% 8 2% 24 3%
Argument Over Words 27 8% 62 13% 89 11%
Jealousy 66 19% 13 3% 79 10%
Because of chores/work 82 24% 131 28% 213 26%
Other 150 43% 239 52% 389 48%
Grand Total 345 100% 460 100% 805 100%
Table 7.5: Why Beaten for Adults or Within Past 3 Years Only
Female Male Grand Total
(n=96 cases) (n=115 cases) (n=211 cases)
Number Percent Number Percent Number Percent
Money 4 4% 4 3% 8 4%
Lover 2 2% 3 3% 5 2%
Jealousy 55 57% 12 10% 67 32%
Words 15 16% 18 16% 33 16%
Chores/wor 5 5% 30 26% 35 17%
kOther 15 16% 48 42% 63 30%
Grand Total 96 100% 115 100% 211 100%
Table 7.6: If Respondent Believes Beating Was Deserved
Female Male Grand Total
(n=345 cases) (n=460 cases) (n= 805 cases)
Response Number Percent Number Percent Number Percent
No 99 29% 56 12% 155 19%
Yes 246 71% 404 88% 650 81%
Grand Total 345 100% 460 100% 805 100%
CARE Leogane & Carrefour Gender Survey 48
Table 7.7: of If Respondent Believes it Was Deserved for Adults or Within Past 3 Years Only
Female Male Grand Total
(n=96 cases) (n=115 cases) (n= 212 cases)
Response Number Percent Number Percent Number Percent
No 61 64% 35 30% 96 45%
Yes 35 36% 80 70% 115 54%
Grand Total 96 100% 115 100% 211 100%
Respondent Violence Against Others
Given the scarcity of survey data on the role of popular class Haitian women as instigators and
even aggressors in violent incidents, we turned the issue around and asked respondents when was
the last time they attacked someone else. In posing the questions we used the colloquial phrase,
denye fwa ou te bay yon moun yon kalot. In light of the cultural-specific emphasis Haitians place
on the word kalot and the aggressiveness and humiliation associated with actually slapping
somone, the most accurate English translation of the phrase is, "the last time you slapped the shit
out of someone." In Table 7.8, we see that for the category, "more than three years ago" men
were twice as likely as women to have "slapped the shit of someone": 6% of men saying that as
an adult but more than 3years in the past they had slapped someone vs. 3% of women who said
so. But for the past three years--the time since the earthquake--the trend changes rather
dramatically. A steady 6% of males still reported having "slapped" someone in the past three
years; but the same number of women, 6%, reported having "slapped" someone. In effect, the
proportion of women who report having violently attacked someone since the earthquake
doubled, reaching the same level of aggression as men report (to 6%). We also see in Table 7.9
that while only 1% of men reported aggression toward their wife or girlfriend, four times as
many women report having attacked their boyfriend or husband (7 versus 33 cases); Overall,
both men and women reported low incidence of violence against unknown members of the
opposite sex, and men are twice as likely to have "slapped the shit" out of another man as women
are to have "slapped the shit" out of another woman. The reasons behind the violence were not
adequately captured in the survey.
Table 7.8: Aggression Against Others by Sex
As and Adult 3 + Within 3 When Respondent
Sex of Respondent Years Past years was a Child Never
Female (n= 820) 2.7% (22) 5.9% (48) 12.1% (99) 79.4% (651)
Male (n =823) 6.1% (50) 6.1% (50) 18.8% (155) 69.0% (568)
Table 7.9: Identity of People Respondents Attacked
Known
Boy/girl friend Stranger but Known but
or Related unspecified Unrelated Unrelated
Sex of Respondent Husband/Wife Female Sex Female Male
Female (n= 820) 4.0% (33) 1.2% (10) 7.2% (59) 6.7% (55) 1.6% (13)
Male (n =823) 0.9% (7) 0.4% (3) 13.4% (110) 1.5% (12) 14.9% (123)
CARE Leogane & Carrefour Gender Survey 49
Rape
Back Ground of the Rape Epidemic
Shortly after the earthquake grassroots organizations such as KOFAVIV began reporting
alarming levels of sexual violence against women (KOFAVI 2010; Amnesty International 2011).
Six weeks after the earthquake, University of Michigan and Geneva Small Arms Survey
conducted an 1,800 household survey and reported that an estimated 3% of all women in popular
neighbors and camps had been raped--in six weeks (Kolbe et. al. 2010). As touched on in the
Review of the Literature, there are grounds to be skeptical of the data-- from both sources.
SOFA and Kay Fanm, two feminist organizations also working in the camps after the
earthquake, report not being able to corroborate the KOFAVIV findings ix The academic
surveyors for University of Michigan and Geneva Small Arms Survey study asked respondents--
strangers to them-- the intrusive question: "Has anyone in the house been sexually assaulted in
the past month?" If the response was positive they asked details. x The first problem with this
approach is the assumption that respondents are going to indulge strangers with accurate details
of sexual attacks on them or their family members. But from the standpoint of accurate data, an
even more pressing problem--for both the survey and KOFAVIV data--comes from the fact that
for 20 years being a rape victim has qualified thousands of impoverished women in Port-au-
Prince to be an aid recipient. Since 1994 a series of USAID, UN, and NGO funded 'viktim'
programs have subsidized women who report having been raped. At its height during the 1990s,
14,000 impoverished female rape victims were on USAID subsidies. The program's economic
impact on the recipients was enough that when the subsidies were suspended--6 years after they
began--thousands of "viktim" marched through the Port-au-Prince streets, some holding placards
that read "Long Live Subsidies for Victim" (see James 2010 for a full description of the
politicization of "viktim" during the 1990s and the subsequent "viktim" movement). Following
the earthquake the move to provide aid and assistance to victims of sexual assault again became
widespread, including US University law professors who went into IDP camps and searched for
rape victims, spreading the word that those who had been raped may qualify for humanitarian
visas (see Fox News 2010). Whether the "viktim" programs were good or bad, appropriate or
misguided, is beside the point; as researchers we cannot responsibly gainsay the impact on
informant accuracy of giving subsidies to a subpopulation of the most impoverished mothers in
the Western hemisphere.
Estimating the Number of People Raped
In an effort to avoid signaling to respondents they may have a chance to capture aid--and to
avoid intruding on their personal lives--we employed a technique different than that used in the
University of Michigan and Geneva Small Arms Survey study cited above. Instead of asking
specifically about the respondent or people in the household, we asked, 'if, since the earthquake,
the respondent knew anyone at all who had been raped.' We operationalized the definition
"know" so that we could use it in a more elaborate statistical inference described shortly.
Specifically, we explained to respondents that what "to know someone" meant was,
1) you recognize the person and the person recognizes you
2) you know their name and they know yours
3) you have talked to them at least once since the earthquake
4) you could contact them now if you needed to
CARE Leogane & Carrefour Gender Survey 50
What we found was that of 1,643 respondents, only 99 (6%) knew anyone who had been raped
since the earthquake. In other words, we found that fewer men and women even knew a person
who had been raped than other studies implied had been raped (Table 7.8).
Table 7.8: People Who Know At Least One Person Raped Since Earthquake by Commune
Commune No Yes
Carrefour 777 57
Leogane 767 43
Total 1544 99
The rape reports were so low and potentially so controversial that after the Leogane survey was
completed, and before the Carrefour survey began, we discussed the issue with CARE staff. We
then sat down with the surveyors and reviewed the question to make sure that there was no
possible misunderstanding about what was meant by "rape" vyol (forced sexual intercourse that
included penetration of mouth, anus or vagina). We also got assurances that they had and would
continue to carefully explain to respondents exactly what was meant by "rape." We also called a
subsample of Leogane respondents on the telephone and explored their understanding of what
"vyol" meant so that we could be sure that we were capturing "sexual attacks." We still got
similar results for both Carrefour and Leogane (Table 7.9). xi
We suspected that maybe the under-reporting of rape had something to do with age categories
and the low numbers of young people in the sample. But as seen in Table 7.9, the frequency of
reported rapes was generally consistent across all age categories. We also recognized that
despite training and despite the heavy emphasis we placed on the importance of the rape
question, it is sometimes the case with politically or morally charged issues that some surveyors
will explain and pursue a question adequately to make all respondents understand; others not
enough; and others tend to cajole answers that would otherwise be negative. In Tables 7.10 it
can be seen that there was indeed variation among the number of positive responses per
surveyor. But even if we were to take the most extreme case and generalize it to all the
surveyors, the results are far less than expected based on reports cited above. Specifically, if we
take the surveyor with the highest reported number of known rape victims (19) and assign the
same result to all the surveyors, we would still get only 16% of our respondents even knowing
someone who had been raped in the 3.4 years since the earthquake--that in areas were as much as
half the entire population was at one time in camps
CARE Leogane & Carrefour Gender Survey 51
Table 7.9: Respondents who Know at Least One Person Raped Since Earthquake by Age
of Respondents (missing = 14)
Number of Female Respondents Number of Male Respondents
Age Categories No Yes Age Categories No Yes
18 to 25 (n=203) 190 13 18 to 25 (n=201) 189 12
26 to 35 (n=205) 187 18 26 to 35 (n=204) 190 14
36 to 50 (n=200) 190 10 36 to 50 (n=209) 201 8
50 + (n=203) 190 13 50 + (n=204) 197 7
All Female (n=811) 764 56 All Male (n=818) 780 43
Table 7.10: Respondents Who Know At Least One Person Raped Since
Earthquake by Enumerator Who Asked the Question
Female Enumerators Male Enumerators
Enumerators No Yes Enumerator No Yes
Female 1 (n=133) 123 10 Male 1 (n=88) 84 4
Female 2 (n=93) 90 4 Male 2 (n=133) 130 3
Female 3 (n=134) 115 19 Male 3 (n=71) 64 7
Female 4 (n=122) 121 1 Male 4 (n=136) 130 6
Female 5 (n=132) 126 6 Male 5 (n=122) 122 0
Female 6 (n=95) 89 6 Male 6 (n=137) 122 15
Female 7 (n=122) 112 10 Male 7 (n=125) 116 8
Estimating the Actual Numbers of People Raped: "Scaling-Up"
The next thing we did was use the intuitively simplistic technique of "scaling up" to estimate the
incidence of rape for the population as a whole. Scaling up was developed by methodologists at
the University of Florida and widely used in estimating unknown populations elsewhere, such as
number of victims of the 1985 Mexican earthquake, illegal immigrant population in California,
population of HIV positive people in New York City and, as with the present study, rape victims
in developing countries (see Killworth et al. 2006). The technique is intuitively simplistic. What
we want to estimate is what proportion of the population has been raped:
1) Our sample statistic for people raped is: "Total number of people that respondents know
who have been raped" (Table 7.11):
2) Our sample population is, "The total number of people that all respondents 'know'", as
defined earlier on (calculated in Table 7.12).
Number of people respondents
know who have been raped" The proportion
of the population
Total number of people that all
= that has been
respondents know raped
CARE Leogane & Carrefour Gender Survey 52
Network Size
The remaining problem is that we must know the average total number of people each
respondent "knows," or what Bernard and McCarty (2009) call network size. To estimate
network size we drew the four most popular names from the survey population list of names.
Because male rape is unreported in this and other surveys in Haiti we restricted our estimations
to the female population. The most popular female names found in our surveys were Darlene,
Nadege, Gerda, and Guerline. From the survey we knew the proportion of people with those
names and so were able to use those proportions to generate secondary estimates of the number
of people a person knows (see Table 7.12). For example, with 10 Darlenes in the total sample
we calculated that 10/1,643 people have that name. Or because it is a female name, 10/820
women have that name. That means that we estimate 1.22% of the female population is named
Darlene. We can generalize from that and expect that if the average person knows 100 women,
then the mean number of Darlene's respondents know will be 1.22. If the average person knows
200 people they will know an average of 2.44 Darlenes. Thus, we can invert the logic and ask
people how many Darlenes they know and then estimate their female network size. To make the
estimate more robust we used four names: Darlene, Guerline, Gerda and Nadege.
With the preceding in mind, we then conducted a random survey of 400 people in the Gender
Survey target areas (200 in Leogane and 200 in Carrefour) and using results from all four names
we calculated the average female network size of at 190.8 people (see Table 7.12)
(sample size) x (the female network size)= (total female population known to respondents)
(1,643 x 190.8) = =313,649
134/313,649= .00043
This is the estimated proportion of the population that has been raped since the earthquake.
To make that estimate comparable to the US rape indices of people raped per 100,000 per year,
we did the following.
• Since the estimation covers the 3.4 years since the earthquake the figure is
divided by 3.4 to achieve an annual rate (.000126).
• Putting this figure into the rates per 100,000 population used in the US to
gauge rape indices, we get a figure of, 12.64 rapes per year (.000126 *
100,000).
• We then divided that figure by 2 because we only calculated females in our
Haiti sample while the US rapes per 100,000 includes males in the total
population figure (12.64/2 = 6.32).
• The result is 6.32 rapes per 100,000 people.
The rape rate for the US in 2010 was 27.3 per 100,000: four times our estimate for Leogane and
Carrefour.
These calculations are only meant to give a general measure of what we found. We have not
calculated variance for the estimate or the confidence interval for the error of the mean. Nor do
CARE Leogane & Carrefour Gender Survey 53
we feel that it is appropriate at this point. This was only an exploratory exercise included as part
of a broader gender study. But the findings should cause us to reconsider just what is going on
regarding the "rape epidemic." Moreover, as seen in the following sections, more general
questions regarding rape and security cast a shadow on the validity of reports and surveys
regarding rape in post-earthquake Haitian and specifically in the communities studied.xii
Table 7.11: Respondents "know" anyone who has been
raped since January 12th 2010 Earthquake and Number
Known*
Total estimated
"Yes" Knows Number of people population of
someone respondent knows "known" people
who has been who have been in sample who
raped raped have been raped
76 1 76
16 2 32
4 3 12
3 5 15
99 135
"know" = 1) you know the person and the person knows you (you
know their name and they know yours'), 2) you have talked to the
person at least once since the earthquake, 3) you could contact
the person if you needed to
Table 7.12: Deriving Average Female Network Size
Names
Measures Darlene Gerta/da Nadege Gerline
Frequency of people with name
in sample of 820 women 10 8 10 9
Proportion in pop with name 0.0122 0.0098 0.0122 0.0110
People with this name per 100 1.22 0.98 1.22 1.10
Observed values in network
2.28 1.85 2.41 2.07
survey
Observed known per 100 people 1.87 1.90 1.98 1.89
Estimate female network size 187.2 189.6 197.7 188.7
We then made network estimates. We took the four most popular female names from the 1,643 sample survey
(they very neatly fell equally in each are, about 4 to 6 occurrences of each of the names in each county). Then
we conducted a 400 person survey (200 in each county) asking people how many women with each name they
know ("know" being operationalized as explained in the main text). That survey was a street survey conducted
in markets and cross roads by interviewing every third person who came by.
CARE Leogane & Carrefour Gender Survey 54
Respondents View on Changing Incidence of Rape
When we simply asked respondents what they thought about the increase in rapes since the
earthquake, 79% of responses from women and 68% of responses from men fell into the
combined categories 'did not know,' 'had not changed,' or 'less since the earthquake' (Chart 7.9).
Chart 7.9: Respondents Evaluations of Rape
Before vs After Earthquake
60% 54%
50% Respondents
40% Female
32%
30% 26% 25% Male
21%
20% 17% 17%
8%
10%
0%
Do not Know More Since the Has Not More Before
N= 1,643
Earthquake Changed the Earthquake Missing = 1
Similarly, when we asked respondents to choose from a list of 5 biggest problems to people's
security, rape was a distant last with 68 (4%) respondents choosing it (Table 7.13).
Table 7.13: Choice of Single Biggest Criminal Problem
Female Male Total
Thievery 512 516 1028
Political Violence 139 101 240
Other 60 125 185
Violation of rights by others 70 52 122
Rape 39 29 68
Grand Total 820 823 1643
Expected Community Reactions to Rape
If the findings reflect what is really going on and there are few actual rapes compared to those
reported by some grass roots feminist organizations and activist-scholars, then at least part of the
explanation for low incidence of rapes may be the expected reaction when violent rape does
occur: 20% of respondents said the likely reaction of people living in their neighborhood to a
rape would be to kill or beat the rapist (Chart 7.11). Moreover, the majority of respondents said
that the greater shame for rape went to the family of the rapist rather than the victim (Chart 7.10).
CARE Leogane & Carrefour Gender Survey 55
Chart 7.10: For Which Family is the Shame Greater: Victim or Rapist
60% 53%
50%
50% Female (n=829,
40% 31% 30% missing =1)
30%
19%
20% 15%
Male (n=823)
10% 1% 1%
0%
Not a Shame Raped Equal Shame Rapist
for the Family
Chart 7.11 Most Likely Reaction to a Rape in the Neighborhood
76%
80% 70%
70% Female (n=829, missing =1) 64%
60% Male (n=823)
50% Total (N=1,642, missin=1)
40%
30% 22%
16% 19%
20% 11%
10% 0% 1% 1% 2% 2% 2% 4% 7% 2% 2% 2%
0%
Security
Responses to questions regarding security echoed the low incidence of sexual assaults seen
above. We asked respondents to choose, "what are the two most serious problems young men
face today?" (Table 7.14). We gave them five choices: 1) getting an education, 2) getting
money, 3) drugs and alcohol, 4) having a pregnant girlfriend and 5) street violence. Violence
came out last, mentioned by only 2% of respondents, less than 1% of men and 3% of women.
Males themselves saw getting money as the biggest problem for young men and then education;
women cited education first and then money as the biggest problems that young men face. When
the question was switched and we asked about the two biggest problems for young women
(Table 7.15), we got similar results regarding the primacy and order of money and education.
The difference was that for women "bearing a fatherless child" was a close third; the threat of
street violence was a greater consideration albeit still relatively small at less than 20%; drugs and
alcohol were much less of a threat; and, somewhat surprisingly, domestic violence was seen as
the least of problems on the list (one likely reason that respondents gave little importance to
domestic violence is that many young women are not yet in union). In summary, if we are to
CARE Leogane & Carrefour Gender Survey 56
take a lesson from our Haitian informants, the biggest problems that young people confront in
Leogane and Carrefour are not the much violence and social afflictions of drugs and alcohol, but
rather getting an education and earning a living.
Tablet 7.14: Two Biggest Problems for Young Men (choices given)
Female Male Total
Education 538 593 1131
Money 574 723 1297
Drugs and Alcohol 466 271 737
Pregnant Girl Friend 130 59 189
Street Violence 25 11 36
(52 extra responses=some surveyors accepted more than two 'biggest problems')
Table 7.15: Two Biggest Problems for Young Women (choices given)
Female Male Total
Education 607 533 1140
Money 478 588 1066
Pregnancy without Spouse 454 321 775
Street Violence 120 58 178
Drugs and Alcohol 38 82 120
Domestic Violence 46 67 113
(54 extra responses because some surveyors took more than two 'biggest problems')
Security and Laws
If it can be said, based on the data seen above, that there is a wide chasm between what many
NGOs, activist-scholars and journalists report regarding violence and insecurity and what people
living in greater Port-au-Prince experience in their daily lives, the same can be said for the
justice system: we found a wide chasm between the 'letter of the law' and what people know
about the law. When we asked if respondents knew about rape laws that have been passed
recently, 90% of them knew nothing at all
about the topic (Chart 7.12). Of the 10% Chart 7.12: Percentage of
who claimed they had heard something Respondents Who Know Nothing of
about a rape law, more than half were Last Rape Law 92%
wrong about when such a law was passed 90% 88%
(Table 7.16). On a more positive note, we
found that more than 95% of respondents
believed that it was illegal for a man to 70%
beat his wife or girlfriend or force her to
have sex; 99% believed that it was also 50%
illegal for a woman to beat her spouse N=1,643 Female Male
(Table 7.17). Also encouraging was that
90% of respondents felt that a woman should report a rape to police (Table 7.18). Perhaps
reflective of the low actual incidence of rape, only 1% of respondents were aware of special
clinics or services for rape victims (1%: Table 7.19), and fully 54% of women said they did not
CARE Leogane & Carrefour Gender Survey 57
know whether services for rape victims were better before or since the earthquake. Of the 24
people who did know about special clinics and services (Tablet 7.20), 9 cited MSF, and 9 simply
said 'clinic.'
Table 7.16: When Respondents Think Last Rape Law Passed
Year Female(n=95) Male (n=67) Total (n=162)
Before 2009 1 37 38
2009 0 6 6
2010 1 3 4
2011 0 7 7
2012 28 7 35
2013 65 7 72
Table 7.17: Respondents Knowledge of Laws Regarding Raping or Beating Girlfriend or Spouse
Female Male Female and Male
(n=820) (n=823) (N=1,643)
Questions Num. Percent Num. Percent Num. Percent
Illegal for Man to Beat Wife 798 97% 795 97% 1,593 97%
Illegal for Wife to Beat Husband 804 98% 816 99% 1,620 99%
Illegal to Force Girlfriend to have sex 789 96% 791 96% 1,580 96%
Illegal for Man to Force Wife to have sex 776 95% 788 96% 1,564 95%
Table 7.18: What a Woman Should If Raped (Choices Given)
Female Male Total
(n=819) (n=823) (N=1,642)
Nothing 5 1% 1 0% 6 0%
See Pastor 1 0% 8 1% 9 1%
Other 41 5% 80 10% 121 7%
Report it to Police 733 89% 753 91% 1486 90%
Go To the Clinic 640 78% 410 50% 1050 64%
Tell Her Family 110 13% 121 15% 231 14%
Table 7.19: Where A Person Can Go For Care In The Area If They Have Been Raped
Female (n=819) Male(n=823) Total (N=1,642)
Church 6 1% 14 2% 20 1%
Special Clinic 15 2% 9 1% 24 1%
Other 76 9% 11 1% 87 5%
Health Clinic 333 41% 304 37% 637 39%
Police 429 52% 435 53% 864 53%
Hospital 407 50% 470 57% 877 53%
CARE Leogane & Carrefour Gender Survey 58
Table 7.20: Special Clinic for
Rape Victims Mentioned
MSF 9
Clinic 9
FFP 1
Diakoni 1
Hospital Vision 1
MOUDHA 1
Other 1
Grand Total 24
Chart 7.13: Comparison in Quality of Services for Rape Victims:
Before vs After Earthquake
Female (n=819) Male(n=823) Total (N=1,642)
60% 54%
50%
40% 35%
32%
30% 25% 26% 27%
22% 21%
16% 17% 17%
20%
8%
10%
0%
Better Before the Has Not Changed Better Since the Do not Know
Earthquake Earthquake
Conclusion
In this section we saw that the expectations regarding high levels of assault against women, rape,
and physical abuse were only partially borne out. Respondents reported that women are thought
of as more often violent aggressors and/or instigators of violence. In 43% of reported cases
where the aggressor was known, the aggressor was a woman and in 53% of cases a man. But the
prominence of women as aggressors has much to do with their role as disciplinarian of the
children. When "beatings" of children were eliminated, 33% of the known aggressors, those who
had attacked adults, were women; 67% were men. There is what could be considered a high
incidence of domestic violence against wives; but we say "could be considered" because if the
figure is indeed representative of domestic violence against women in the area it is a rate lower
than any country in the Western hemisphere and half the US rate seen in the Review of the
Literature. Domestic violence appears to occur more often in lower income households.
However, women who suffer beatings at the hands of spouses and lovers more often appear to
be, not the most disenfranchised women, but those who make financial contributions to the
household, something that is perhaps related to defending or asserting ones rights. As for extra-
domestic sexual violence against women and a post-earthquake "epidemic of rape": our research
in Leogane and Carrefour suggests that there was not one.
CARE Leogane & Carrefour Gender Survey 59
8. Family, Partners, Children, and Sex
In the Review of the Literature it was seen that researchers have often presented Haitian culture
as male centric, women as sexually repressed, and teenage pregnancy rates as high. There is also
the understanding that Haitians eschew contraceptives, believing they cause illness and that men
often insist their wives do not use them. Less studied issues are current attitudes toward abortion
and child birth. In the Leogane and Carrefour surveys we asked questions pertaining to all these
issues.
Opinions on who is more in Need of Sex
To begin we asked respondents who needs sex more, men or women. In Chart 8.1 more than half
of both men and women said that both have equal sexual needs.
Chart 8.1: Who Needs Sex More, Men vs.
Women by Sex of Respondent
70% 66%
60% 51% Female Respondent
50% Male Respondent
40%
28% 30%
30%
20% 15%
10% 4% 2% 3%
0%
Both the Same Men Women Do Not Know
N=1,643
Appropriate Age at onset of Sexual Activity
To gain an understanding of when respondents thought a boy/man versus girl/woman should
begin having sex we expected, based on pretests, that age would be only one criteria. Other
considerations were if a person was still in school, if they had a job, and if they were married or
had a stable, income earning and responsible partner. We accepted only one response. Among
them we accepted the common response, "when they are ready," something that in view of
accepting only one response obscures the analysis because what the respondent meant could fall
into any of the other categories: when they were finished with school, when they have income,
when they are 18 years old, or when they have found a suitable spouse." Nevertheless the results
are informative.
As seen in Tablet 8.1, next page, the majority of respondents felt that both boys and girls should
wait until they are 18 years old to begin having sex: specifically, 67% of respondents said that
girls should wait until 18 years of age and 59% of respondents said that boys should wait.
However, women placed less emphasis on 18 years of age and greater emphasis on having
income, finishing school, or being prepared. Female emphasis on waiting was especially
pronounced regarding boys having income: 17% of female respondents said so versus 6% of
male respondent.
CARE Leogane & Carrefour Gender Survey 60
Table 8.1: When Should Boys vs. Girls Become Sexually Active
Reponses for When Girls Should Reponses for When Boys
List of Possible Become Sexually Active Should Become Sexually Active
Responses Female Male Both Female Male Both
Age younger than 18 2% 3% 3% 4% 6% 5%
18 + years 57% 77% 67% 50% 68% 59%
When Ready 18% 11% 14% 18% 12% 15%
When has Income 9% 2% 5% 17% 6% 12%
Finishes School 8% 3% 6% 6% 2% 4%
Marries 5% 2% 4% 3% 2% 3%
When Wants 0% 2% 1% 1% 4% 2%
Other 0% 0% 0% 0% 0% 0%
Total 100% 100% 100% 100% 100% 100%
N=1,643
Teen Pregnancy
Notwithstanding the widespread concern among NGOs and activists for high rates of
teenage pregnancy in the wake of the earthquake, Haitians tend to be sexually conservative. As
seen in the Review of the Literature, Haiti has one of the lowest teenage pregnancy rates in the
Western hemisphere: half or less that of several Latin America countries, less than half that of
the Dominican Republic, only about 25% higher than overall the US teen pregnancy rate, and
one third the rates for both US Blacks and US Hispanics (also see WHO 2007; UNFPA 2007;
WHO 2001; Planned Parenthood 2011; OAH 2013; also see Endnote ii).
Although there was certainly what researchers for Potofil (2012) called a post-earthquake "teen
pregnancy bubble," young women 18 to 25 years age in our Carrefour and Leogane samples also
have relatively low rates of childbirth, especially in view of high overall birth rates. Inferring
from the totals in Table 8.5, young Leogane and Carrefour women in the age group 18 to 25 year
annually give birth to 93 children per 1,000 women. In comparison, the rate for Dominican
teenage girls 15 to 19 years of age is 104 per 1,000 girls, or an overall average of .52 children per
teenager (World Bank 2011). In other words, Dominican teenagers 15 to 19 are having more
children than Leogane and Carrefour women in the larger and older 18 to 24 years age category.
Teen Pregnancy in Leogane and Carrefour Sample vs. in the United States
Overall, the average age at first birth for all mothers in the sample was 24.2 years of age; 17.9%
of the women sampled who had born children had their oldest living child at 19 years of age or
less. If we correct the figure for a 2006 EMMUS 10.3% infant and child mortality rate, then the
combined number of Carrefour and Leogane female respondents who bore their first child while
still a teenager is 18.4%, slightly less than the 20.7% of US women who reported in 2011 having
given birth as teenagers (Planned Parenthood 2012). xiii
CARE Leogane & Carrefour Gender Survey 61
Table 8.2: Children Born to Respondents 18 to 25 Years Old
Sex Countryside Peri-Urban City Total
Female 0.79 0.79 0.59 0.75
Male 0.38 0.34 0.15 0.30
Childbirth & Conjugal Unionxiv
In Tables 8.2, above, and Table 8.3, right, we
see that a significantly greater number of Table 8.3: Percentage of Respondents per
women in our sample become mothers at Age Groups who Have Children
younger ages than their male counterparts; or Age Groups Female Male
put another way, men in our sample do not
18 to 25 51% 18%
begin fathering children until much later in life
than women. We can also infer from the data 26 to 35 81% 68%
that 4/5ths of children are the offspring of men 36 to 50 97% 89%
36 years of age and older, precisely those men 50 + 94% 94%
who by virtue of years working and Total 81% 68%
accumulated wealth have greater resources to
share with women. In Chart 8.12, it can be
seen that the relationship is, for the sample size,
statistically significant.
Chart 8.2: Comparison of Statistical Significance for
Average Number of Partner-Parents if Respondent
3.00 has Children: Men vs. Women (p < .05)
2.50
2.00 Missing
2.16 36
1.50 1.52 1.72
1.62 1.45
1.39 1.60
1.21 1.27 1.34
1.00
0.50
0.00
CARE Leogane & Carrefour Gender Survey 62
Pro-Natalism: Children and Fertility
We saw in the Review of the Literature that Table 8.4: Whether People Need Children
Haitians tend to express a high degree of what Sex of Respondent No Yes Total
is called pronatal attitudes, meaning they favor Female 2 818 820
child births. Similarly, in our samples, only 2 Male 29 794 823
women and 29 men said that people did not Men and Women 31 1,612 1,643
need to have children (Table 8.4). Out of 1,643 respondents not a single respondent said that the
ideal number of children was zero (Table 8.5); Table 8.5: Average of Ideal Number of Children
the average ideal number of children was Age Groups Female Male Both
(N=1,643)
moderate ~2.5, a figure consistent across both 18 to 25 2.51 2.55 2.53
age groups and sexes (ibid). Compared to 26 to 35 2.57 2.52 2.54
findings in rural areas elsewhere and surveys 36 to 50 2.55 2.69 2.62
conducted in the past this represents a 50 + 2.59 2.65 2.62
significant shift toward lower ideal family size All Age Groups 2.56 2.60 2.58
(see for example Schwartz 1998, Maynard-Tucker 1996).
In Table 8.6, we give the actual figures for number of children born to males versus females per
age group, by degree of urbanization, and by the number of children desired. It can be seen that
there is neither an apparent nor a statistical difference in how many children respondents say
they want and how many children respondents actually have. Nor are there differences between
the age and sex the respondents and how many children they say they want.
Table 8.6: Children Born to Men and Women by Age and Sex
Age Countryside Peri-Urban City Total
Sex Group Actual Ideal Actual Ideal Actual Ideal Actual Ideal
18 to 25 0.79 2.55 0.79 2.59 0.59 2.49 0.75 2.55
Female 26 to 35 2.05 2.69 1.93 2.56 2.07 2.27 2.00 2.57
36 to 50 3.70 2.58 3.42 2.53 3.23 2.51 3.49 2.55
50 + 4.44 2.62 3.83 2.64 4.16 2.53 4.18 2.61
18 to 25 0.38 2.58 0.34 2.44 0.15 2.67 0.30 2.55
Male 26 to 35 1.50 2.53 1.45 2.53 0.85 2.57 1.31 2.54
36 to 50 3.04 2.87 2.94 2.59 2.51 2.65 2.87 2.70
50 + 5.41 2.61 4.96 2.61 4.80 2.84 5.09 2.67
One reason that there are no age groups or differences by sex for the number of children desired
may have to do with the disposition of those sampled to respond to the question. In past surveys
researchers have sometimes found that Haitian respondents report lower ideal fertility to avoid
jinxing their chances of having many children or in an attempt to tell researchers what
informants think is the politically correct response (Schwartz 2000). With this in mind, we tested
if informants really favored smaller family size by adding the question, "a family with three and
a family six children, which is better off?" Only 30 respondents chose the family with six
children: 10 men and 20 women (Chart 8.2 and Table 8.7, next page).
CARE Leogane & Carrefour Gender Survey 63
For the 1,613 people who had chosen the family with three rather than six children, the reason
given was overwhelmingly because children were too expensive (Table 8.9). This is a radical
difference from what was found 13 years go in Jean Rabel, Haiti where over 50% of respondents
chose a family with 6 children (see Schwartz 2009). Comparatively, in Leogane and Carrefour
it does appear that there is a growing, or extant anti-natal trend. Or, for those who prefer, a trend
toward less children, and perhaps greater investment in those that are born.
Table 8.7: Family of 3 vs. 6 Children
Chart 8.3: Respondents who Say a Family Family Females and
with 3 vs. 6 Children is Better Off Sizw Female Male Males
Six 20 10 30
Three 800 813 1613
n =30 Total 820 823 1643
n = 1613
Table 8.9: Reasons for Choosing
Family with 3 Children
Table 8.8: Location of People who Favor Reasons Female Male Both
Family of 6 vs. 3 Children Life is Too Expensive 629 751 1380
Location Number of Respondents Too Many Problems 133 52 185
City 3 Not Enough Time 14 7 21
Countryside 10 Other 24 3 27
Peri-Urban 17 Grand Total 800 813 1613
Preference for Boys vs. Girls
A commonly used indicator of the degree to which females are repressed and discriminated
against in different cultures is preference for boys over girls. In all the cross cultural
questionnaires discussed in the Section 3, Methodology, there were questions designed to capture
male preference. In the Leogane and Carrefour survey we too asked about sex preference.
However, during pre-tests we realized that when we ask respondents directly which sex of
offspring they preferred many tended to avoid responding or to respond that both sexes were
equally desirable. Therefore, instead of asking directly about son/daughter preference, we
presented respondents in the survey with the hypothetical scenario of a family with three girls vs.
a family with three boys and asked which they thought would be better off. Girls came out on top
(Chart 8.3). Women favored the family with girls at a ratio of 3 to 1; men favored the girls at a
less dramatic ratio of 11 to 9 (ibid). The relationships were consistent no matter if the
respondents lived in rural, peri-urban or urban areas (Chart 8.4 & 8.5), The outstanding reason
given for why they chose the family with girls had to do with the role that females play in the
household (Table 8.10). For those who chose boys, the outstanding reasons were that males bring
in more money followed by the security that comes with the presence of older boys (Table 8.11).
CARE Leogane & Carrefour Gender Survey 64
Chart 8.4: Family with 3 Girls vs. 3 Boys
(All Respondents )
80%
70%
60% 75%
50% 65%
40% 55%
30% 45%
20% 35%
10% 25%
0%
Female Male Male & Female
RespondentsThree Girls
Three Boys
Chart 8.5: Preference for Family with 3 Girls vs 3 Boys
(Female Respondents)
100%
80%
60% 72% 76% 74%
40%
20% 28% 24% 26%
0%
City Countryside Peri-Urban
Three Boys Three Girls
Chart 8.6 : Preference for Family with 3 Girls vs 3 Boys
(Male Respondents)
60%
50% 57% 56%
53%
40% 47%
43% 44%
30%
20%
10%
0%
City Countryside Peri-Urban
Three Boys Three Girls
CARE Leogane & Carrefour Gender Survey 65
Table 8.10 Reasons for Preferring Girls
Respondents
Female Male Both
Girls Better Care for the Family 218 192 410
Girls Manage the Household 72 169 241
Boys Cost Too Much 177 16 193
Girls Are More Loyal 40 30 70
+Other 55 3 58
Girls Bring in More Money 16 17 33
Girls Attract Loyalty of Men 9 22 31
Girls Do Better in School 25 5 30
Grand Total 612 454 1,066
Table 8.11: Why Boys
Respondents
Reasons Female Male Total
Boys Work Harder 54 216 270
Boys Provide Physical Security 74 46 120
Boys Bring in More Money 25 63 88
Other 28 10 38
Boys Do Better in School 18 19 37
Girls Cost Too Much 9 15 24
Grand Total 208 369 577
Abortion and Contraceptives
The inverse of the pronatal attitudes discussed earlier are "anti-natal" attitudes and practices that
mitigate against fertility and child birth, most notably abortion and use of contraceptives. Legally
abortion in Haiti has always been and continues to be illegal. Critics of the law have implied that
it is an example of gender discriminatory legal system. But as seen in the Literature Review, the
law has seldom been officially enforced. Censorship of abortion has come largely from the
general population, both males and females. Aborting a fetus has traditionally been criticized as
the "worst sin" and severely censured through social ridicule (see Schwartz 2009). To get an
ideas of contemporary attitudes in Leogane and Carrefour and to gauge whether they are too are
changing, as appears to be the case with desire for fewer numbers of offspring, we including
relevant questions in the surveys. xv
We asked respondents if they believed abortion was justifiable in any of the cases listed in Table
8.12 (following page). We then combined the responses to create an index of tolerance: We
classified as "Intolerant" all those respondents who said that abortion was never justifiable. We
classified as "Moderately Tolerant" those respondents who accepted abortion only in conditions
of Rape and/or Medical Complication. And we classified as "Tolerant" any respondent who
accepted that a woman could justifiable abort a pregnancy in the case of Rape and/or Medical
Complication and at least one of the following: 'has no spouse,' 'is still in school,' 'is too young,'
'has too many children,' 'is too poor,' or 'other.'
CARE Leogane & Carrefour Gender Survey 66
What we found was that 61% or more of all
women and men are at least moderately Table 8.12: Frequency of Reasons For
tolerant of abortion; for men the figure was Justifiable Abortion
the same, 61% (Table 8.13, Chart 8.15). The Choices Female Male Total
trend changes with age and sex: young Other 2% 2% 2%
women are the most tolerant and women No Spouse 3% 3% 3%
over 50 years of age the least tolerant. Still i n School 4% 5% 4%
Too Young 5% 7% 6%
One caveat in assuming that this is evidence
Too many Children 10% 6% 8%
of changing fertility patterns and a shift to
Poverty 6% 14% 10%
more anti-natal behaviors and attitudes is
Rape 13% 13% 13%
that at least one other study in Haiti found
that older women favor larger numbers of Medical 30% 24% 27%
children more than any other age-sex Never Justifiable 27% 28% 28%
category. The reason was because older
women control the household, depend on the labor of children in accomplishing subsistence
tasks and freeing themselves to engage in income generating itinerant marketing endeavors
(Schwartz 2000). Nevertheless, together with declining ideal fertility levels seen above, the
overwhelming preference for three children vs. six children households, the increasing tolerance
of abortion suggests a radical change from past pronatalism. Corroborating the existence of this
trend is the wide acceptance and favorable view of contraceptives seen in the next section.
Table 8.13: Tolerance for Abortion
Tolerant
(unmarried, still in school, Moderately Tolerant Intolerant
poor, too many children) (medical & rape) (never Justifiable)
Age Groups Female Male Female Male Female Male
18 to 25 51% 35% 15% 25% 34% 40%
26 to 35 29% 40% 38% 23% 33% 37%
36 to 50 20% 35% 41% 31% 39% 34%
50 + 25% 28% 27% 25% 49% 47%
Total 31% 35% 30% 26% 39% 40%
Chart 8.7: Analysis of Age by Tolerance of
Abortion
60%
48%
44%
37% 36% 36%
40% 33% 32% 35%
27% 27% 25% Most Tolerant
19% Tolerant
20%
Intolerant
0%
18 to 25 yrs 26 to 35 yrs 36 to 50 yrs 50 + yrs
CARE Leogane & Carrefour Gender Survey 67
Contraceptives
In Tables 8.14 & 8.15 it can be seen that 3/4ths of respondents view contraceptives favorably
with favor and certainty most elevated in in younger age groups. This too is a radical break from
past studies where as many as 85% of all women were found to view contraceptives in a negative
light (Schwartz 1998). A counter intuitive trend in this respect is that a greater proportion of
male and female respondents living in rural, versus urban areas, view contraceptives favorably:
the figures for females were 56% for urban respondents, 63% for peri-urban respondents; and
75% for rural respondents (Charts 8.6). The figures for males were 59% for urban respondents,
74% for peri-urban respondents, and 75% for rural respondents (Charts 8.7). Finally, in Table
8.16 we see that there is little difference in the opinions of respondents whether a man or woman
has a right to use contraceptives even without the consent of their spouse.
Table 8.14: Count of Contraceptive Good vs. Bad by Sex of Respondent
Female Male Male and Female
Do Not Know 19% 13% 16%
Mostly Bad 13% 15% 14%
Mostly Good 66% 70% 68%
Not Better or Worse 2% 2% 2%
Table 8.15: Contraceptive Good vs. Bad by Age of Respondent
18 to 25 26 to 35 36 to 50 50 + All Ages
Do Not Know 14% 10% 13% 26% 16%
Mostly Bad 16% 15% 13% 12% 14%
Mostly Good 68% 73% 72% 60% 68%
Not Better or Worse 2% 2% 2% 2% 2%
Chart 8.8: Proportion of Respondents Qualifying
Contraceptives as "Mostly Good"
(Female Respondents: (p < .05)
90%
80%
74%
70%
63%
60%
56%
50%
40%
30%
20%
10%
0%
City Countryside Peri-Urban
CARE Leogane & Carrefour Gender Survey 68
Chart 8.9: Proportion of Respondents Qualifying
Contraceptives and "Mostly Good"
(Male Respondents: (p < .05)
90%
80%
70% 74% 74%
59%
60%
50%
40%
30%
20%
10%
0%
City Countryside Peri-Urban
Table 8.16: Opinions on Man and Woman Right to Use
Contraceptives with Spousal Consent by Sex of Respondents
Woman Has Right Man Has Right
Respondents No Yes No Yes
Female (n=820) 64% 36% 65% 35%
Male (n=823) 68% 32% 67% 33%
Male and Females (N=1,643) 66% 34% 66% 34%
9. Family Support
In preparing the survey we were also interested in personal support networks: who men and
women turned to when they needed material assistance; who they turned to when they need
emotional support or advice or moral support; and differential attitudes or mother and fathers
regarding the quality of relationships with their children and with one another. We present the
results below.
Quality of Family Relationships and Support
Opinions on Quality of Relationships to Partner and Children
We found that women in our samples rate their relationships to their spouses with less
enthusiasm than did men: 13% of women rated their relationship with their partner as "Very
Good," while 50% of men rated their relationship in this way (Chart 9.1). Women also rated their
relationship to their children less enthusiastically than did men,. 19% of women said they had a
"Very Good" relationship with their children. 44% of men said so (Chart 9.2).
CARE Leogane & Carrefour Gender Survey 69
Chart 9.1: How Women and Men Rate Relationship
with Their Partner
60%
50%
50%
41% Female
40% (n=498)
30% Male
30% 26% (n=470)
20%
20%
13%
10%
10% 6%
2% 2%
0%
Very Bad Bad OK Good Very Good
Chart 9.2: How Women and Men Rate Relationship
with Their Children
60%
51%
50% 44%
Female
40% (n=658)
26% 28%
30% Male
24% (n=558)
19%
20%
10%
3% 3% 3%
0%
0%
Very Bad Bad OK Good Very Good
Who Respondents turn to for Material Support
When it comes to material aid, what we see in Table 9.1 is that in the case of a need for money or
food, men report depending on brothers more so than any other category (23%), a figure cited
almost twice as frequently as the next category, that of spouse (12%). Men depended as much on
CARE Leogane & Carrefour Gender Survey 70
their sisters (12%) as their spouses, followed closely by their mothers (11%). At a total of 23%
mentions, sisters and mother combined are as important a source of material aid for men as
brothers. Brothers, sisters, and mothers combined, were the first people men reported turning for
material air for 46% of respondents.
Women on the other hand reported turning far more frequently to their spouse for material aid;
19% said so, a tendency that echoes the socially constructed gender expectations discussed in the
Review of the Literature, i.e. men should provide money to women for household maintenance
and commercial enterprise but that women are expected to reciprocate not with money but with
sexual and domestic services. The next person women most frequently reported turning to was,
similar to reports for men, that of brother (14%). Also as with men, mothers (13%) and sisters
(11%) ranked high as first source of aid; and at a combined 24% of mentions they exceeded any
other category. Similar to men, if we combine brothers, sisters and mothers, 48% of women
reported turning to them first for aid.
Who Respondents turn to for Moral Support/Advice
In Tablet 9.2 we see that for advice, or what we can interpret as psychological support, men turn
most often to friends (26%) then brothers (13%), and then spouses (12%) followed by mother
(11%) and then more distantly, sister (6%). At a rate equal to men (26%), women too reported
turning most often friends for psychological support, followed by spouse (19%) then brother
(10%), mother (7%) and finally sister (6%).
Table 9.1: First Person Respondent Goes to Table 9.2:
if Needs Material Aid 1 Count of Need Advice
Relationship to Female Male Relationship Female Male
Respondent (n=820) (n=823) to Respondent (n=820) (n=823)
Grand Father 0% 0% Grand Father 0% 0%
Grandmother 0% 0% Grandmother 1% 1%
Cousin 1% 3% Uncle 2% 5%
Uncle 2% 3% Cousin 3% 5%
Aunt 3% 3% Father 3% 8%
Daughter 5% 1% Daughter 5% 1%
Son 5% 1% Aunt 5% 3%
Father 5% 5% Son 5% 1%
Friend 8% 10% Sister 6% 6%
Sister 11% 12% Brother 7% 13%
Mother 13% 11% Mother 10% 11%
Brother 14% 23% Spouse 19% 12%
Spouse 19% 12% Friend 26% 26%
Other 14% 13% Other 7% 7%
CARE Leogane & Carrefour Gender Survey 71
10. NGOs, Hospitals, and Clinics
Membership in Organizations
In Table 10.1 and Charts 10.1 to 10.3, we see that, as expected from the gender defined political
roles of men in Haiti seen in the Review of the Literature, men are more prominent than women
in organizations and leadership of organizations. But two points are noteworthy. First, while less
frequently than men, women do have a presence as members and leaders of organizations; and
second, they are more prominent than men, at least in terms of numbers, in churches, far and
away the organizations in the survey areas with the most membership.
Table 10.1: Group Membership by Type of Group and Sex of Respondent
Organization Female Male Total
Church 65% 52% 59%
Youth Group 6% 4% 5%
Development Association 1% 6% 4%
Women's group 4% 0% 2%
Peasant Association 1% 3% 2%
Camp Association 2% 1% 1%
Artisan association 1% 1% 1%
Mother's club 1% 0% 1%
Voudou Association 0% 0% 0%
SRV 0% 1% 0%
Musical, social or athletic 0% 0% 0%
Political Party 0% 0% 0%
Savings Group 0% 0% 0%
None 30% 37% 33%
Chart 10.1: Member of At Least Chart 10.2: Member of At Least
One Organization One Organization
(Including Church) (excluding church)
80% 70% 15% 12%
64%
10%
60% 5%
5%
40% 0%
Female (n=820) Male (n=823) Female (n=820) Male (n=823)
CARE Leogane & Carrefour Gender Survey 72
Chart 10.3: At Least One Official
Position in an Organization
30% 23%
20% 16%
10%
0%
Female (n=574) Male (n=523)
NGO and State Sponsored Seminars since the Earthquake
To evaluate the extent to which NGOs and the Haitian State have reached out and informed the
population we asked respondents if they have attended a seminar since the earthquake, and if so
what type of seminar and who sponsored it. What we found was that about 18% of respondents
had attended at least one seminar (Chart 10.4); attendance was about equal for men and women
(18% vs.17); the frequency of attendance was almost 4 times greater in the town of Leogane than
in the City of Carrefour (28% vs. 8%); the vast majority of the seminars had to do with disaster,
cholera or other health issues (Table 10.2); and the Haitian State, the Red Cross, and CARE were
believed to be the most common sponsors--each with 45 citations (Table 10.3).
Chart 10.4: Attended At Least One Chart 10.5: Number of Seminars
Seminar Since Earthquake Respondents have Attended Since
28% Earthquake
30%
1500 1350
25%
20% 18%
1000
15%
8%
10% 500
5% 110 63 54 66
0% 0
Carrefour Leogone Total 0 1 2 3 4+
Chart 10.6: Attended At Least One Chart 10.7: Attended At Least One
Seminar Since Earthquake Seminar Since Earthquake by Sex and
25% Commune
150 111 112
20% 18%
17% 100
40 30 Female (820)
15% 50
0 Male (823)
10% Carrefour Leogane (809)
Female (n=820) Male (n=823) (n=834)
CARE Leogane & Carrefour Gender Survey 73
Table 10.2: Types of Seminars Respondents Table 10.3: Seminar Sponsors
Attended Since Earthquake
Type of Type of Number of
Seminar Freq Seminar Freq Seminar Sponsors Mentions
Hlth, Nut. & Handicap & State (FAES, MSPP, ASEC) 45
Hygiene 94 Stress 5 Red Cross 45
Emergency Mother's CARE 45
medical 71 Club 5 USAID 29
Other 71 Business 4 Tear Fund 15
Cholera 69 Savings 4
OIM 15
Building
Johanniter 13
construction 53 Environment 3
Oxfam 13
AIDS 37 Democracy 3
Disaster 32 Filiaris 3 ACTED 7
Education 30 Drainage 2 Envangelicals 5
Livestock & Mother Child SAVE 5
Garden 12 Health 1 MSF 4
GBV 8 Sanitation 1 Samaritan's Purse 3
Water 7 World Vision 3
CARITAS 2
Habitat 2
MUDHA 1
ACDI VOCA 1
CORDAID 1
Scouts 1
Other (orgs mentioned once) 38
Illness and Use of Hospitals, Clinics, and Doctors
Illness is a big part of the lives of the respondents and their families. When asked, 'when was the
last time someone in the household was,' in the opinion of the respondent, "seriously ill.' Fully
47% replied "this month"; 74%% said within the past two months (Table 10.4). It was most often
a child in the house who was sick (Table 10.5); and women were more often ill than men (ibid).
Symptoms were predominantly fever (Chart 10.8); most people were taken to or sought out on
their own some form of treatment, usually a hospital visit (Chart 10.9); 11% more Carrefour
versus Leogane respondents (81% vs. 70%) reported the sick individual went to the hospital,
difference that was statistically significant (Chart 10.10); and for those who did not go to a
hospital, clinic or doctor the primary reasons given was that "it was not necessary," followed by
"too far" and "too expensive" (Table 10.6). Women in the house were considered more
knowledgeable than men in recognizing and responding to illness by only a slim ratio of 6 to 5
(Table 10.7).
CARE Leogane & Carrefour Gender Survey 74
Table 10.4: Last Illness in the House (N=1,643)
When Households Cumulative %
This Month 47% 47%
Last Month 22% 69%
Two Months Ago 5% 74%
Three Months Ago 4% 78%
Four Months Ago 3% 81%
Over Four Months Ago 10% 91%
Never 9% 100%
Table 10.5: Who Was Sick (n=294)
Females Males
Person Households Person Households
Aunt 1 Uncle 1
Grandmother 3 Grandfather 2
Sister 12 Husband 5
Mother 13 Father 8
Wife 16 Brother 15
Respondent Female 47 Respondent Male 38
Daughter 73 Son 60
Total 165 Total 129
Chart 10.8: Symptoms/Disease When Person Was
Last Sick
Fever 558
Stomach Ache 174
Flu 161
Sorcery 52
Diabetes 51
Heart Troubles 49
Injury 47
Cholera 43
Malaria 4
Other 504
0 100 200 300 400 500 600
CARE Leogane & Carrefour Gender Survey 75
Chart 10.9: Where the Person was Treated
Nowhere 30%
Hospital 29%
Healer 10%
Clinic 6%
Doctor Private Practice 6%
0% 5% 10% 15% 20% 25% 30% 35%
Chart 10.10: Use of Hospital for Last Illness in
the House: Carrefour vs Leogane (p > 95%)
86%
81%
81%
76%
70%
71%
66%
61%
56%
Carrefour Leogane
Table 10.6: Reasons Given for
Not Going to Hospital, Clinic or
Doctor
They do not give good care 1%
Don't like being touched 3%
It was not open 3%
Too Expensive 11%
Too Far 30%
Not necessary 52%
CARE Leogane & Carrefour Gender Survey 76
Table 10.7: People Respondents Identified As Most
Knowledgeable Regarding Illness in the House
Men Women
Grand Father 1 Grandmother 3
Uncle 9 Sister 25
Brother 19 Daughter 27
Son 24 Aunt 31
Father 53 Wife 48
Husband 78 Mother 178
Respondent Male 508 Respondent Female 505
Total 692 Total 817
Pre-Natal, Birth and Use of Services
The vast majority of women (654 of 752 or 88%) sought out professional medical care during
there last pregnancy, most (55%) at a public hospital (Chart 10.11). The proportion of
respondents who visited different practitioners were approximately equal in Leogane and
Carrefour (Chart 10.12). Of the 98 (12%) who were not attended to by professionals, 50%
explained that it was too far and 43% too expensive (Chart 10.13). The number of respondents
who gave birth at home was 17% greater in Leogane (53% vs. 36%), a difference that is
statistically significant for the size of the sample (Chart 10.14).
Chart 10.11: Pre-Natal Care: Where
Respondent Consulted Last Time Pregnant
Public Hospital 55%
Clinic 16%
Midwife 9%
Doctor Private Practice 6%
Nurse 1%
None 7%
Other 6%
0% 20% 40% 60%
CARE Leogane & Carrefour Gender Survey 77
Chart 10.12: Use of Pre-Natal Services:
Carrefour vs. Leogane
51%
Nurse 59%
13%
Midwife 19%
Other 6%
8%
Clinic 6%
7% Leogane
Doctor Private Practice 13% Carrefour
3%
None 9%
3%
Public Hospital 2%
0% 20% 40% 60% 80%
Chart 10.13: Reasons Respondent Did Not
Consult Last Time Pregnant
Too Far 50%
Too Expensive 43%
It was not open 5%
Don't like being touched 2%
0% 5% 10% 15% 20% 25%
Chart 10.14: Birth at Home: Carrefour vs.
Leogane (p < .05)
80%
60%
53%
40%
36%
20%
0%
Carrefour Leogane
CARE Leogane & Carrefour Gender Survey 78
Post-Natal Care and Use of Services
We found similar results for post natal care (Chart 12.15). The majority of women sought out
professionals (92%), most at a clinic, or with a visiting midwife or nurse (81%). Respondents in
Carrefour reported using professional hospital and clinic services more than those of Leogane
(12.16), a difference that was not statistically significant (Chart 12.17) For the 5% of the total
sample that did not use professional services the explanations were more varied than those for
pre-natal care: 38% explained that the service was not available ('not open'), 30% that the
treatment they received was bad ('they are rude' and 'not good care'), and in contrast to pre-natal
care only 17% cited expense and distance -- a consequence of the women not having to go all the
way to the hospital (Chart 12.17).
Chart 10.15: Post Natal Care: Where
Respondent Consulted Last Time Gave Birth
Health Clini 48%
Midwife 17%
Nurse 16%
Doctor Private 8%
Public Hospital 6%
No one 4%
Other 2%
0% 10% 20% 30% 40% 50% 60%
Chart 10.16: Use of Post-Natal Services:
Carrefour vs. Leogane
45%
Health Clinic 52%
Midwife 13%
22%
Nurse 20%
11%
Doctor Private 9% Leogane
6%
Public Hospital 6% Carrefour
6%
No one 5%
2%
Other 3%
1%
0% 20% 40% 60%
CARE Leogane & Carrefour Gender Survey 79
Chart 10.17: Respondents who did not use any
Post-Natal Specialist Last Pregnancy:
Carrefour vs. Leogane (p < 95%)
10%
5% 5%
2%
0%
Carrefour Leogane
Chart 10.18: Post Natal Care: Why Respondent
did not Consult at Clinic or with Doctor
It was not open 38%
They do not give good care 15%
They are rude 15%
Too Expensive 9%
Too Far 8%
Don't like being touched 1%
Other 15%
0% 10% 20% 30% 40%
CARE Leogane & Carrefour Gender Survey 80
11. Conclusion and Recommendations
If we were to expand on Lowenthal (1986) and Richman's (2003) descriptions of gender
relations in Haiti, seen at the beginning of this report, and conceive of them as a male vs. female
'field of competition' for access to resources, control of households and members, and control
over household finances and budget, then the present study suggests females win. Women make
significant contributions to household finances, they are arguably as powerful as men in the
domestic sphere, they appear more autonomous than men with regard to personal decisions (such
as joining organizations or traveling), they exercise a high degree of control over other members
of the household, and men and women both prefer daughters. We expected to find some of these
trends, but we were generally surprised by the extent to which women in the samples appear to
be on par with men. A noteworthy inequity is that women in the samples were significantly less-
educated than men, something that does not correspond to national samples. But even on the
most worrisome issues, most notably with respect to violent rape, women come out far less
abused than claimed in most reports from NGOs, newspapers, and gender-based activist
organizations.
Some aid practitioners might find these conclusions disturbing. They may either dismiss them or
they may wonder why NGOs, international organizations and donors have been devoting so
much attention to empowering Haitian women if they are already empowered. We believe the
lesson should be, not to reduce development efforts that target women, but rather to focus less on
Haitian women as victims, acknowledge their power, and move on to more fully mobilizing them
as vectors in development. With that said, we offer the following general recommendations
Mobilize: We should focus on mobilizing women to get more involved in the one area where
they are most conspicuously absent: local level politics and community development. CARE and
other NGOs have an advantage in accomplishing this because international development and
health oriented organizations are among the most economically and socially influential
opportunities available. Locals working in the sector earn two to eight times the local wage rates
and they preside over social organizational and infrastructural improvement projects that give
them inordinate status and prestige in their communities.
To mobilize women, CARE should take a two pronged approach. 1) bring in consultants with
local knowledge and language skills who understand UNICEF sponsored SEED-SCALE
approach to bottom up development and 2) identify credible feminist organizations.
SEED-SCALE
If we have learned anything from the past 70 years of development it is that purely top down
initiatives seldom succeed (Easterly 2006). The point is especially poignant in Haiti (Schwartz
2008). UNICEF funded SEED-SCALE provides an alternative (Taylor et. al.). Whether it is
health, education or community driven infrastructural development SEED-SCALE is a powerful
approach to building enduring bottom up community-NGO-State organizational alliances that
resolve community problems, and empower women (see http://www.seed-scale.org for SEED
SCALE kit and see Taylor et al 2012 for description of process and examples).
CARE Leogane & Carrefour Gender Survey 81
Gretchen Berggren Ph.D. at Harvard, Bettie Gebrian PhD, and University of Connecticut
Professor Judy Lewis are three consultants with a combined 100+ years of experience in Haiti
and authors of several successful community health programs in the country, including several at
Albert Schweitzer in the Artibonite and USAID funded Haiti Health Foundation in the Grand
Anse. It is recommended that CARE hire the consultants for an exploratory evaluation of the
Carrefour and Leogane program with the prospect in mind of incorporating SEED SCALE
organization building strategy.
Identify credible partners: As Alexis Gardella wrote 7 years ago in her USAID Gender
Assessment,
Haiti has an impressive and rich community of organizations that are dedicated to
effecting change, from human rights, to women’s rights, to domestic violence and
illiteracy. Groups concerned with all the aspects of women’s status already exist, both
within and outside Port-au-Prince, and many have consolidated their advocacy efforts
under umbrella organizations or associations. Every major women’s advocacy group in
Port-au-Prince has extensive ties to regional and rural associations. There is no issue
identified in this assessment that does not already have a collection of advocacy groups
mobilized around it. (Gardella 2006: 29)
That being said, it must be admitted that during the past 50 years of intense foreign aid, while the
Haitian economy has gone into a dizzying free-fall, the Haitian landscape of grassroots
organizations and NGOs has become infested with entrepreneur minded opportunists. This is not
entirely bad. Partners and aid practitioners, whether foreign or local, should be able to earn a
living and feed their families. But CARE must avoid the opportunists who seek money only and
identify credible NGOs. Two are SOFA and KAY FANM: powerful and credible organizations
with credible leaders, a long history of positive involvement in representing Haitian women, and
extensive networks in both rural and urban areas. CARE should ally with these organizations.
Combat Misinformation: CARE should combat misinformation. Misinformation is the means
by which money is misdirected. It causes organizations such as CARE to waste time, effort and
money channeling resources into areas where they are not needed and, by corollary, away from
areas where they are needed. It deprives needy and vulnerable people of help they might
otherwise receive. It cheats donors out of their hope that their money would be well spent and
CARE out of the satisfaction that we are accomplishing our mission. In its ugliest forms it is
frequently used means by which criminals capture aid funds meant for their own enrichment and
abuse the very people we are trying to help, as with the orphan director who sexually molests the
children under his care or the sociopath turned pastor who builds network of businesses and
finances his way into a position of political power. Misinformation also sabotages the endeavor
to empower and mobilize women.
One rather innocent example of misinformation is the assumption that female-headed household
are in greater need than Male-Female Headed households. While it is probably true that young
mothers are in greater need, the notion that females headed households as whole are
CARE Leogane & Carrefour Gender Survey 82
disadvantaged appears specious and founded on assumptions and may be leading aid agencies to
categorically eliminate many of the most needy households while scheduling aid for other that
least need it.
A more extreme and potentially dangerous example of misinformation is the "rape epidemic"; if
it is largely a fabrication of entrepreneurial minded advocate-aid workers, grassroots
organizations, and sensationalizing journalists, then no better example of feminine self-sabotage
exists. If we are indeed dealing with a fabricated crisis, the greatest impact the "rape epidemic"
has had may be to have made violent rape seem to be a common and expected behavior in
popular neighborhoods and by implication, no cause for great alarm. In other words, before it
has even occurred, we have desensitized the population, the authorities, and donors to the most
aggressive and demeaning form of attack on the traditional pillar of the Haitian family and
society: women, poto mitan.
Young Males
We found no evidence in our study that female headed households were less well-off than those
with both a male and female head. We did not find evidence that men were repressing and
controlling their wives any more than vice versa. We did not even find evidence of inordinate
levels of domestic abuse or rape. But times are indeed changing. Haiti is in the throes of a
transition from a rural society governed by tradition and social censure to an urban society
governed by formal laws and enforced by a formal justice system. At the moment formal laws
discriminate against women. The low level of female participation in politics is unmistakable.
These issues should be addressed. The relatively powerful traditional position of Haitian women
in the rural economy should be preserved and the way paved for them to assume a greater formal
role in future Haitian society. But in addressing these issues and the growing dangers to women
and girls we should be careful not to neglect the significance of other populations and, in doing
so, make matters worse. Specifically, Gardella warned in her 2006 study of a growing population
of bored, uneducated, and economically desperate young men – the most dangerous of these can
become grossly empowered through crime and participation in narcotrafficking. In the words of
Gardella:
In the current socio-political climate in Haiti, the most important population at risk is
certainly urban male youth, i.e., urban gangs. The criminal and political activities of these
gangs is of such a degree as to destabilize the major and secondary metropolitan areas, and
all attendant economic activities, and to further jeopardize the installation and proper
functioning of the newly elected government. [2006:30]
With the preceding points in mind, it would behoove us to remember that gender is not just about
females. Gender encompasses “the economic, social, political and cultural attributes and
opportunities associated with being male and female.” It is in understanding the dimensions of
CARE Leogane & Carrefour Gender Survey 83
relationship between males and females that we can more effectively target development
initiatives to bring about a safer, more secure, and healthier environment for everyone.1
1
Definition of Gender was taken from Gardella (2006) who is citing the Development
Assistance Committee Guidelines for Gender Equality and Women’s Empowerment in
Development Cooperation. OECD: Paris (1998).
CARE Leogane & Carrefour Gender Survey 84
12. Notes
i
The causes underlying the outstanding role of women in popular Haitian culture is surely linked to the country's
regionally unique economy and prevailing subsistence strategies. For two hundred years Haiti has been a regional, if
not global anachronism. While neighboring countries became or remained oriented toward plantation and latifundia
systems, within 30 years of its 1804 independence Haiti had evolved into a nearly full-blown peasant economy
dependent on small garden plots equitably distributed among 10s of thousands of farming families; while
neighboring countries became or remained export and import oriented, Haiti depended and still largely depends on
local petty production organized around households and regional rotating marketing systems; while neighboring
countries became mechanized, Haitian farmers and craftsmen depended and still largely depend on pre-19th century
technology as well as human and animal labor power; while most neighboring countries have experienced
demographic transition to lower birth rates, the process has been much slower in Haiti where many women,
particularly those living in rural areas, continue to bear children at rates equal to the highest in the world and the
highest biologically possible (see Schwartz 2000). Linked to these economies, land tenure systems, and subsistence
strategies, Haiti was also unique in the degree to which it has depended for foreign revenue on male labor migration.
For over 100 years a Haitian male right-of-passage included migration to plantations in Cuba and the Dominican
Republic. More recently men and an increasingly number of women migrate to work in to areas of intense hotel
construction, fishing grounds, and touristic zones. The traditional pattern was for men to migrate to get the money to
set spouses up in homes and to invest in expanded household enterprises such as peasant agricultural, livestock
rearing, craft production, and commerce. The frequent absence of men encouraged and conditioned the prominent
role of women seen earlier and gave them an edge in the "field of competition" that Lowenthal described.
ii
Specifically, teen pregnancy rates vary widely by race and ethnicity. In 2008, the pregnancy rate for non-Hispanic
white teens was 43.3 per 1,000 women 15–19 years of age. Depending on which of the cited sources is used, the
pregnancy rate for Hispanic teens was 106.6. For African-American teens it was 117, with a upper level for 2006 of
126 for both. "See page 2 of the Planned Parenthood Fact Sheet, by the Katharine Dexter McCormick Library
Planned Parenthood Federation of America OAH (Office of Adolescent Health) 2013 Trends in Teen Pregnancy
and Childbearing.
Table 12.1: Selected Latin American and Caribbean Adolescent Birth Rates
(births per annum per 1,000 women in age category: World Bank 2013)
Country 2008 2009 2010 2011
United States 38 36 33 30
Hispanics* - - - 106
African Americans* - - - 117
Trinidad and Tobago 34 33 33 32
Grenada 41 40 38 37
Haiti 45 44 43 42
Cuba 45 45 44 44
St. Vincent & Grenadines 58 57 56 55
Chile 58 57 57 56
Guyana 65 63 60 57
St. Lucia 60 59 58 57
Paraguay 71 70 69 68
Colombia 73 72 71 69
Jamaica 76 74 73 71
Panama 81 80 79 77
Ecuador 82 82 81 81
Honduras 92 90 89 87
Guatemala 106 105 104 103
Dominican Republic 108 107 106 105
CARE Leogane & Carrefour Gender Survey 85
*Planned Parenthood Fact Sheet, 2012
iii
Researchers who have treated the topic at length have argued that pronatalism in Haiti derives from the need for
children as a mechanism of old age security (Murray 1977), from cultural values left over from slavery (Maynard-
Tucker 1996), poor healthcare system (Smith 1998), as deriving from insensitive and even rude doctors and nurses
(Maternowska 2006); and even deriving from the economic contributions that children make to the household
survival strategies (see Schwartz 2009). But few if any have found that males are the cause of low contraceptive use
among women.
iv
The exact quote, "Contre toute attente, on constate que les femmes qui participent le plus fréquemment aux sept
décisions et qui sont le moins fréquemment exclues de toutes ces décisions sont les femmes du milieu rural et celles
qui ont le moins d’instruction. Par contre, les femmes qui travaillent pour de l’argent participent beaucoup plus
fréquemment que les autres aux prises de décision." [EMMUS 2000: 247].
v
At least part of the reason that gender in Haiti has been misconstrued can be attributed to generalizing developing
world gender relations among the middle and upper classes to the working classes living in popular neighborhoods
and living largely within the informal sector. The popular classes have dense social networks where the same people
know and interact with each other on many levels. The women are in the market together, their children are in
school together, they all go to the same funerals, the same weddings and baptisms, their husbands work together,
play dominoes and soccer together. Larger families mean geometrically greater number of kinship ties. In the case of
urban neighborhoods they live in densely packed neighborhoods. There are few secrets and exponentially greater
social censure than in the middle class residential families where a man can begin to abuse, intimidate and
eventually graduate to beating his wife in the seclusion and privacy of the family home, with no one to check his
behavior and no other men or other women to run to her defense. The Haitian man embedded in the formal sector
can then get up the next morning and go to work with people who do not know his wife, go to the gym with an
entirely different social set that also do not know her. In other words, he doesn't have to face up to what he did. Add
to this greater male access to jobs and higher male salaries that come with a nascent formal sector; add middle class
social stigmas that constrain women sexually but liberate men, meaning that a middle or upper class Haitian woman
can destroy herself socially by engaging in a sexual liaison with any man socio-economically beneath her while her
husband's sexual liberty and access to women of all classes means he is less dependent on her emotionally or
sexually; add the transition from a traditional agrarian and/or household based economy with its informal legal
system and social censure to a formalized legal system that has not yet been adapted to dealing with gender and
abuse of women that occurs privately. What all this means for the Haitian woman in the formal sector is that that
she is more, not less, dependent on a man. She does not even have the lower class Haitian woman's right to engage
in extra-marital liaisons when her husband fails to take care of her financially. Isolated residentially, checked with
social stigmas, with no option of a career in the informal economy, and unprotected by a nascent formal justice
system, the middle class woman still has the burden of rearing the children but without the extended family and
neighbor support characteristic of popular neighborhoods.
vi
Official unemployment rates for Haiti vary between 70 to 80 percent (World Bank 2010a). Similarly,
organizations such as the World Bank (2010b) have estimated that over 50% of the Haitian population lives on less
than $1 per day and as much as 80% lives on less than $2 per day. Such figures are sometimes discussed in the
context of a "living wage" for one Haitian worker and three dependents of US$29.00 per day (Solidarity Center,
2011). In coming to understand seemingly contradictory reports of income and cost of living, and in putting into
perspective analysis in the following pages, a couple ethnographic realities should be understood.
First off, most of the eighty percent of the "unemployed" Haitian population is hard at work in a vibrant informal
sector and the thriving internal domestic marketing and service economy. Haitians work in the informal sector as
night watchman, yardman, maid, cook, nanny, teacher, policeman, guard, porter, butcher, baker, tailor, basket
maker, rope weavers, carpenter. mason, iron smith, mechanic, electrician, plumber, radio technician, typesetter,
copier, and painter. They make nets, weirs, boats, beds, latrines, roofs. They work in domestic healthcare industry
as nurses, doctors, herbal and spiritual healers and priests. They work as sea captains, mariners, and boatswain in the
thriving mostly informal domestic shipping sector and drivers and truck loaders and fee collectors on the thousands
CARE Leogane & Carrefour Gender Survey 86
trucks that carry goods throughout Haiti. Tens of thousands work as drivers on the moto-taxis that fill the streets,
back roads and paths of the country. They distill alcohol and make comestibles from small candies to prepared nuts,
fish, fried snacks, and meals sold in street restaurants. And they work as vendors selling everything from the
ubiquitous corner stall peddling a single cigarette and shot of rum to telephone recharge cards to hair ties to small
bags of water to cures for aids and cancer and unrequited love and bad luck or dozens of different lottery tickets.
More than 50% of them farm and/or fish. And almost every one of them is engaged not in a single one of these
occupations, but several.
Many of the occupations mentioned above are for men, but some are un-expectantly female--such as butchers and
fish processers. Women will perform most farming tasks. Women are masseuses and midwives. They exclusively
monopolize the ownership and management of popular restaurants. Although men make some comestibles, most
production of candies and other treats are female enterprises. But more than anything else, women completely
dominate the movement and redistribution of domestic produce. Those who are members of farming households are
thought of as the owners of the produce from their husband's gardens. They harvest and sell the produce and with
the money invest in the purchase and resale of the produce that other women harvest and they so dominate this
sector of the economy--trade in domestic produce-- that middle aged woman are often equal or more economically
powerful than their husbands.
For those men and women who can't find a place among the occupations listed above men pursue income in
seasonal farming, fishing, transport, and construction sectors and they migrate to the Bahamas, the Dominican
Republic, Canada and the United States where they engage in any number of occupations, not least of all the sex
industry and narco-trafficking. Women migrate to the same places where they work in factories or as cooks, nannies,
maids, prostitutes or masseuses or bar girls. Haitian women also make a strong showing in the neighboring
Dominican Republic's international marriage market where each year thousands of them marry foreigners and fly off
to join the North American and European middle and upper classes.
Most of these occupations described above are petty income opportunities, many of them, such as midwifery or rural
construction are not fulltime but rather intermittent opportunities. Others such as selling candies or weaving are
ongoing activities that complement other endeavors and may yield as little as US $1 per day. For fulltime
occupations the minimum wage is 200 gourdes (~ $5) for most formal sector workers and 125 gourdes (~ $3.00) for
apparel workers in trade free zones. Farmers throughout the country consistently pay their neighbors 150 gourdes
per day ($3.00)--that is 25 gourdes more than minimum wage-- for what they call a jouné, 6 hours of intense
agricultural labor. If they provide a meal they pay 100 gourdes ($2.50). On a higher level it is noteworthy that
skilled artisans earn about US $10 per day.
The key to understanding how people survive in Haiti on below "living wage" salaries is the role of the household as
a social security mechanism and productive unit. Households pool labor and resources to lower individual costs of
living and to enable members to survive difficult times. As seen in subsequent section on the household, even very
young members of the household may contribute to livelihood security by fetching fire wood and water, running
errands, selling goods by the street or out of the home, washing clothes, and preparing meals. Perhaps more
importantly than anything else in understanding the household as the basis for livelihood strategies and the role that
children play is that for both urban and rural areas children stay home and perform basic domestic tasks and care for
younger siblings thereby freeing their old sisters, cousins, aunts and mothers to engage in itinerate trade and go to
urban areas to work as domestics.
The charts below are meant to give the reader a sense of income per occupation in Haiti in the formal vs. the
informal sector. Although the data did not come precisely from the survey sites some of the informal sector data
was gathered in Carrefour and other research conducted by the consult corroborates that they are applicable in the
area and other urban and peri-urban areas of the country, making the information is useful when assessing the
relative economic resources per skill category for Leogane and Carrefour.
CARE Leogane & Carrefour Gender Survey 87
Table 12.2: Formal Sector Employment (USD) Table 12.3: Mostly Employment
(Demattee 2012) Informal Sector (EFI 2013)
Occupation Year Day Occupation Year Day
Maid $2,177.00 $7.26 Domestic/hm $1,170.00 $3.90
Guard $1,734.00 $5.78 Guard/home $1,012.50 $3.38
Unskilled Labor $2,419.00 $8.06 Unskilled Labor $1,125.00 $3.50
Driver $5,347.00 $17.82 Driver $3,150.00 $10.50
Nurse $10,150.00 $33.83 Nurse $2,790.00 $9.30
Office Staff $6,548.00 $21.83 Receptionist $2,500.00 $8.33
Mechanic $10,801.00 $36.00 Mechanic $4,125.00 $13.75
Doctor $28,306.00 $94.35 Doctor $10,350.00 $34.50
Table 12.4
Entrepreneurial Sector
Occupation Year Day
Call-Card V. $1,500.00 $5.00
Shoe Shine $1,875.00 $6.25
Load Truck $2,250.00 $7.50
vendor food $2,250.00 $7.50
Artisan $3,000.00 $10.00
Mason $3,750.00 $12.50
Moto Taxi $4,125.00 $13.75
Small Vendor $4,500.00 $15.00
Restaurant owner $9,000.00 $30.00
Taptap Taxi $9,000.00 $30.00
vii
Table 12.5: Chi Square for Who Wins Arguments
Asymp. Sig.
Value df (2-sided)
Pearson Chi-Square 294.476 15 .000
Likelihood Ratio 273.119 15 .000
Linear-by-Linear
66.673 1 .000
Association
N of Valid Cases 1404
CARE Leogane & Carrefour Gender Survey 88
viii
All the preceding should be interpreted with a caveat: few respondents condone violence against spouses. As
seen in Tables 8.3 on page 26 and in Table 8.7 and 8.8 below, while there may be a de facto high level of violence
against women in union, very few respondents condoned violence against wives, girlfriends or lovers.
Table 12.6: Respondents who Say that Woman Has
Right to Beat Other Woman or Husband if He has
Affair (N=1,643)
If she Right to Beat Other Woman 6%
If she Right to Beat the Husband 9%
Table 12.7: Respondents who Say that Man has Right
to Beat Spouse if she has an Affair (N=1,643)
If he has the right to beat her 6%
ix
Personal interview with director Olga Benoit of SOFA and Marie Yolette Andree Jeanty of Kay Fanm 2/2/2012
x
Kolbe et. al.'s (2010) post earthquake survey is by far the most extreme estimate of sexual assault in post-
earthquake Haiti. Because it was sponsored by the University of Michigan and Geneva Small Arms Survey it is also
the one that lent the most credibility to the claims of a rape epidemic. A published academic article on the survey
findings, authored by Kolbe and a collection of 6 University Professors and one Haitian Survey supervisor
concluded that in the six weeks following the survey, "Approximately 3 per cent of the general population sample
reported being a victim of sexual violence since the earthquake; all but one case involved female victims." (page 3).
There are reasons to question validity of the results and the care with which the survey was conducted, if it was
conducted at all.
The survey was based on follow-up visits to people interviewed two months prior to the January 12th 2010
earthquake when Kolbe supervised a survey of 1.800 Port-au-Prince households. Six weeks after the earthquake the
researchers sent the same interviewers to visit the same respondents to evaluate post earthquake conditions and
incidence of crime. This was a moment in time when 30% to 40% of the Port-au-Prince population was living in
camps, another 25% had fled the capital for the countryside, and 10% had left for Miami and the Dominican
Republic. Kolbe et al claim to have successfully located and interviewed 93% of the original respondents, a feat
accomplished in the space of two weeks. It was from this survey that Kolbe et. al. concluded that 3% of the
population had been sexually assaulted; considering that all were women and half the survey population was male
this means that estimate is really 6% of the survey population sexually assaulted. Clearly something is amiss. There
are other flags: the researchers also concluded from the data that 6x as many children had been killed in the
earthquake; yet a University of Miami study found there were more adult than child causalities. They also found that
children were 11 times more likely to have died of injuries after the quake; yet a CDC study of survival rates in
improvised post-earthquake hospitals found more adults died and what we know medically is that that children are
more likely than adults to survey traumatic orthopedic injuries and to recovery more rapidly.
See, Kolbe, Athena R., Royce A. Hutson , Harry Shannon , Eileen Trzcinski, Bart Miles, Naomi Levitz d , Marie
Puccio , Leah James , Jean Roger Noel and Robert Muggah 2010 Mortality, crime and access to basic needs before
and after the Haiti earthquake: a random survey of Port-au-Prince households In Medicine, Conflict and Survival
For Kolbe and Muggah's death rate for injured children 11x that of adults see Surveying see, Kolbe, Athena R. and
Robert Muggah 2010 "Haiti’s post-quake needs: a quantitative approach" Humanitarian Exchange Magazine ISSUE
48
CARE Leogane & Carrefour Gender Survey 89
xi
The definition for many respondents is wide, capturing attacks that are and are not sexual, meaning that likely
misunderstandings would include assaults of a non sexual nature.
xii
In assessing the significance of the estimates, we can expect that many people who have been raped do not report
it to the authorities or friends. But in assessing the results note that it is comparable to alleged reports to surveyors
who knock on doors and ask perfect strangers if anyone in the house has been raped. In both cases we are dealing
with what can be considered known rapes. Moreover, in Haiti, where the population density is high and so are social
networks, anonymity and secrets are not kept as well as in developed countries. Moreover, in assessing these results
note that the survey was conducted in Leogane, the epicenter of the earthquake, and Carrefour, a highly urbanized
region of Port-au-Prince that is closest to the epicenter, one of the most damaged areas, and an area where IOM
reported 6 months after the earthquake over half the population living in IDP camps, that still has the 4th highest
IDP population in Port-au-Prince (14 months after the earthquake IOM reported 14% of Carrefour population still
living in camps). Yet we found no evidence that rapes in Carrefour and Leogane were even close to the rate in the
United States; we found no statistical differences between Carrefour and Leogane. Moreover, even if we were to
assume that the actual number of rapes was four times that reported in the surveys it would only then equal the US
rate and still throw the reports of the extensive violent rape into question.
xiii
We correct the figure with an adjusting for 'infant mortality' because 'age at first birth' is derived from oldest
living child.
xiv
Insight into patterns of conjugal union in the area can be n examination of number of children born to men and
women in lieu of number of partner-parents (how many fathers or mothers respondents had the children with), and
ethnographic data from elsewhere gives. Specifically, we found that 1,216 of the 1,643 respondents in the survey
had children. There are more mothers than fathers (660 mothers vs. 556 fathers). There are also more children born
to mothers than fathers (2,060 vs. 1,942). In theory, this excess number of births among mothers and lower overall
number of fathers could he attributed to women bearing greater numbers of children with partners from outside the
survey areas. Experience suggests that this is not the case (Schwartz 1998; Murray 1977). Moreover, if we assume
that the tendency for males and females parenting with people in the area is equal, the findings fit the expectation
that a minority of fathers either a) do not recognize their children, b) the mothers do not inform or allow the fathers
to claim paternity, or c) paternity is unknown. Thus, statistically speaking and all things being equal, what we find is
that 109 of the 3,967 children born to our respondents have no father (Table 8.7).
The preceding figure of fathers less children is much lower than many would expect given high number of reported
fatherless children from organizations such as UNICEF (which by inference estimated in its 2004 Children on the
Brink Report that as many 1 in 10 Haitian children were fatherless). But it is surely concealed in part by a
countervailing adaptation on the part of women to their monopoly over reproduction and the opportunity to assign
paternity. A certain proportion of mothers assign paternity to multiple fathers. One study suggested that 13% of all
children in a rural village had multiple fathers (Schwartz 2000). This is not unique to this village and certainly not
unique to Haiti alone, but it does appear to be a pronounced and institutionalized pattern for at least of minority of
Haitian women in rural areas and popular urban quarters. An ethnographic parallel to women assigning paternity to
multiple fathers it is the fictive illness known as perdsisyon --technically known as 'arrested pregnancy syndrome--in
which women are believed to carry a fetus for as long as five years. Both men and women widely accept the disease
as legitimate--a national study found that as many as 8% of women claim to have suffered the affliction (Barnes-
Josiah et al 1996)--and it allows women to dupe their husbands or lovers into accepting paternity for children that do
not biologically belong to them
Knowledge of perdisyon, the tendency for some women to assign paternity to multiple fathers and the culturally
expected role of men to give money and support to women who have their children, helps inform some findings in
the gender survey. First of all, Haitian women tend to marry up in age, as evident in the significantly greater number
of women in union at lower age groups; and we can infer from the data in Table 8.5 thru 8.8 that 4/5ths of children
are the offspring of men 36 years of age and older (see also Chart 8.10 & 8.11), precisely those men who have
greater resources to share with women who are fathering them. In Chart 8.12, it can be seen that the relationship is,
for the sample size, statistically significant.
CARE Leogane & Carrefour Gender Survey 90
xv
Cases documented of women being caught aborting children and punished with humiliation tactics such as being
tied up in the market and having the "crime" broadcast over a megaphone (Schwartz 2000). Contraceptives too have
traditional been informally sanctioned, women who use them being thought of as promiscuous and women warned
away from using them with the belief that they will become sick and that contraceptives are a developed world plot
to limit the number of Haitians on earth (ibid). These beliefs fit into what has been called Haiti's "pronatal socio-
fertility complex," an array of mutually reinforcing beliefs that assure high fertility, even among young women who
may not want to bear children (ibid). With this in mind, we fully expected to find that respondents overwhelmingly
abhor abortion and contraceptives. We got something different.
13. Annex: Questionnaire
Questionnaire English
(Questions are not in the order asked but arranged for convenience of category)
Introduction
Hello, my name is ________ I am working on a survey for CARE International. We are
conducting research to better understand relationships between men and women in the area. We
would like to ask you some questions. Your identity will be confidential. You are free to refuse
to give me an interview and if you decide to give the interview free to refuse to respond to any
questions. Do you agree to do the interview? ( if yes, signs consent form). Yes No
Orientation
Choose the community where the respondent lives Kafou Leogane
Locality?
That is, City Suburb Town or village Country
Enumerator choose your name
Janvier Judithe Emile Marckenson Previlon Renaud Fils Sonia Sabine Vilfort
Prophete Sylvestre Lacombe Dieula Remy Odile Simon Joana Joseph Ricardo
Vernet Darline Intervol Jude Egain Ambeau Emile Pharrel Vilfort Judith
Respondent
CARE Leogane & Carrefour Gender Survey 91
Respondent's last name?
Your first name?
Telephone number
Sex? Fi Gason
Where were you raised? Here Elsewhere
Where where you born? Artibonite Centre Grand Anse .....
At what age did you move here?
Age now?
Education?
Other education or training?
All income earning activities?
Number of children?
How many living brothers and sisters do you have on your mother's side?
How many living brothers and sisters do you have on your father's side?
How many of them live close enough that you can seek their assistance when you need them?
If you have a problem with money or not enough food in the house, who do you first go to for
assistance? My mother My Father My Grandmother ....
And if you need advice for a personal problem you are having, who do you usually go to first?
My mother My Father My Grandmother My Grandfather My son.....
CARE Leogane & Carrefour Gender Survey 92
Household
Who is the household head? Myself Woman of the house Man of the house ...
Gender of household head Gason Fi Gason ak Fi
How many people live in the house (sleep here more often than elsewhere)?
Girls 0 to 5 years of age 0 1 2 3 4 ....
Boys 0 to 5 years of age 0 1 2 3 4 ....
Girls/women 6 to 25 years of age 0 1 2 3 4 ...
Boys/men 6 to 25 years of age 0 1 2 3 4 ....
Women older than 25 years of age 0 1 2 3 4 ....
Men older than 25 years of age 0 1 2 3 4 ...
How many children who sleep in the house are not family of any one else in the house?
How many adult servants do you have/employ?
Do you and your family own this house? Yes No
Do you and your family own the land? Yes No
Roof type? Thatch Tin Concrete Tarp Wood Other
Toilet? Flush Toilet Block outhouse Wood outhouse Hole Nothing Other
Source(s) of electricity? Nothing Grid Generator Invertor Solar panel
What fuel do you most often use to cook food? Wood Charcoal Gas
Primary drinking water? Bottle water We treat it Water as it is Other
Where does the household get it's general purpose water? Cistern at the house ......
CARE Leogane & Carrefour Gender Survey 93
How far in minutes is it?
Who is the primary bread winner? My self My mother My Father ....
What is his/her primary occupation? Salaries work Commerce .....
Second primary bread winner? My self My mother My Father ....
What is his/her primary occupation? Salaries work Commerce .....
Who is the primary manager of the household budget? My self My mother .....
Does anyone in the house own a motorcycle taxi? Yes No
Do you personally have another business? Salaries work Commerce ....
How much do you do you spend average per day on food for the household meal(s)?
Do you personally, do you own any of the following? Land Livestock Furniture.....
Since the earthquake (douz janvie), has anyone in your family taken your money, land or
anything else you owned without your agreement or consent? Yes No
How many people in the house are in school?
Who does the following tasks: (girls, boys, all children, men/man, women/woman....)
• Fetches water?
• Washes clothes?
• Wash dishes?
• Cleans house?
• Makes food?
• Watches the children?
• Takes the children to school?
• Buys at the local store?
• Buys in the market?
• Works outside the home?
• Makes daily decisions about what to cook for meals?
• Makes big decisions regarding purchasing land, transportation, or other
investments
• Makes the final decision regarding who sleeps in the house?
• Works the hardest?
CARE Leogane & Carrefour Gender Survey 94
Medical
When a child is sick who best knows what to do? My self My mother ....
When was the last time someone in the house was sick? This month Last month ...
What did they have? Cold/flu fever stomach ache injured ...
Where did you first seek help? other Private doctor Clinic ...
And after that where did you go other Private doctor Clinic ....
Independence
If you want to go visit a friend or family who lives far away, do you need to ask permission from
someone else in the house? Yes No
And if you want to join a group (such as a woman's group or hang out with your friends), do you
need to ask permission from someone else in the house? Yes No
When you and your partner disagree, who usually wins?
Myself My partner Don't have partner Compromise -
NGO Data
Since the earthquake, how many NGO seminars have you attended?
Are you a member of any of the following organizations.......
Do you hold an official position in the organization? Yes No
Now I'm going to pose some hypothetical situations and I would like you to tell me your
opinion.
If a mother has a daughter who is 16 years of age and the mother discovers that the girl is having
sexual relations with a boy of 16, what should the mother do if the girl is still in school?
Go on with life Speak to him/her Beat him/her Support him/her Call the police
Other
CARE Leogane & Carrefour Gender Survey 95
And if she is not in school? Go on with life Speak to him/her Beat him/her Support
him/her Call the police Other
And if the girl is in school and the guy she is having a relationship with is 35 years old, but he
has the means to take care of her, what should the mother do? Go on with life Speak to
him/her Beat him/her Support him/her Call the police Other
And if the girl is not in school? Go on with life Speak to him/her Beat him/her
Support him/her Call the police Other
Sex
Who needs sex more?
male female both the same don't know
At what age should a female begin to have sexual relations?
12 years of age 13 years of age 14 years of age 15 years of age 16 years of age
17 years of age 18 + years of age When he/she wants Whe he/she is ready When
he/she finishes school When he/she finds someone When he/she had a job When he/she
marries Other
At what age should a male begin to have sexual relations?
12 an 13 an 14 an 15 an 16 an 17 an 18 + an Lè li vle Lè li pare
Contraceptives
In general, is there more good associated with contraceptives or more bad?
More good More bad Same Don't know
Why do you say more good? Regulate number of offspring Avoid disease Other
Why do you say more bad? It makes you sick People criticize you It is for sleazy people
Do you think that a woman has the right to decide not to have children even if her husband wants
children? Yes No
Do you think that a man has the right to decide not to have children even if his wife wants
children? Yes No
CARE Leogane & Carrefour Gender Survey 96
Abortion
In which of the following situations would you say that it is justifiable for a woman to have an
abortion?
medical condition in case of rape too young still in school no spouse too poor
too many children never other
Fertility and Family
How many children should a couple have? 0 1 2 3 4 5 6 7 8 9 10
11 12 13 14 15+
If a couple has 6 children and another couple has 3 children, who's usually better off?
Six Three
If a couple has 3 girls and another couple has three boys, who is better off?
Three girls Three boys
Do people need to have children? Yes No
According to you, what is the most important reason a woman should chose a husband?
Love Money Character Family Education Religion Hard worker Faithful
Responsible Other
And what is the second most important reason? Love Money Character Family
Education Religion Hard worker Faithful Responsible Other
And if the man is poor, what advice would you give a woman?
stay with him ignore it other
According to you, what is the most important reason a man should chose a wife?
Love Money Character Family Education Religion Hard worker Faithful
Responsible Other
And what is the second most important reason? Love Money Character Family
Education Religion Hard worker Faithful Responsible Other
Who most needs the other more?
Husband more needs his wife Wife needs her husband more Both need the other same
CARE Leogane & Carrefour Gender Survey 97
And you, could you live your life without a spouse? Yes No
How would you qualify you current relationship with your spouse? Very good Good ok
not good terrible
How would you qualify you current relationship with your children? Very good Good
ok not good terrible
Violence
With which statement to you most agree? Women more often incite men to violence or
initiate a physical fight with women or Men more often incite violence against women or
beat them without good cause
If a man beats a woman and she didn't deserve it, what is the punishment that he should get?
nothing prison fine be allowed to hit him/her back ask forgiveness other
If a woman beats a man and he didn't deserve it, what is the punishment that he should get?
nothing prison fine be allowed to hit him/her back ask forgiveness other
The last time someone beat you up or attacked you, where was it?
never this year last year three years ago more than three years ago when I was a
child
Who beat you?
My mother My father My grandmothe r My grandfather Husband Wife
Girl/boy friend Brother Sister Aunt uncle cousin Nothing to me Police
Teacher My child other
Why did they beat you?
for words over work over a lover jealous over money other
Do you think that you deserved it? Yes No
The last time you 'slapped the shit out of someone', when was it?
never this year last year three years ago more than three years ago when I was
a child
CARE Leogane & Carrefour Gender Survey 98
Who was it? Husband boy/girl frirn Wife Brother Sister Cousin Nothing to
meWhy? for words over work over a lover jealous over money other - Go
With respect to the law, police and justice, is it legal for,
A man to beat his wife?
A woman to beat her husband?
For a man to force his girlfriend to have sex when she doesn't want to?
For a husband to force his wife to have sex whe she doesn't want to?
Do you remember when the last time it was that they passed a new law regarding rape?
Security
In the following list, what two biggest problems do you think that young women have these
days?
Education Job/money Pregancy Insecurity/crime Domestic violence Drugs and
alcohol
In the following list, what two biggest problems do you think that young men have these days?
Education Job/money Insecurity/crime Domestic violence Drugs and alcohol
If we were not talking about crime, what is the biggest problem you think that we have in the
country today? Thievery Violence Rape Political turmoil Other
Rape
I would like you to consider all the people you know. What do I mean when I say "know." 1) you
know the person and the person knows you (you know their name and they know yours'), 2) you
have talked to the person at least once since the earthquake, 3) you could contact the person if
you needed to
Now, do you "know" anyone who, since the earthquake, has been raped? Yes No
If, yes, how many people do you know who have been raped?
If a woman is raped, what should she do?
nothing call police tell my family go to the clinic go see people at church other
CARE Leogane & Carrefour Gender Survey 99
If a man is raped, what should he do? nothing call police tell my family go to the
clinic go see people at church other
Where should a person go if he or she is raped? hospital health clinic church police
special clinic other
How do you see the way police handle rapes cases?
they can make matters worse they do nothing they should know I don't know
If you compare the situation now with the way it was before the earthquake, do you think that the
services for rape victims are better or worse?
better now same as before worse now I don't know
Do you think there that was more rape before the earthquake or more now?
more know more before earthquake same I don't know
According to you, which is the greater shame, to have someone in your family who has been
raped or someone who has raped another person?
rapist victim same shame it's not a shame for the family
And if someone were to rape a woman in this neighborhood, what yo think your neighbors
would do about it?
Go on with life Call the police Call the sheriff Beat him Kill him Talk to his
family Other
Take GPS reading
CARE Leogane & Carrefour Gender Survey 100
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