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  • 1. Kelly Hallman Population Council New York Tel: + 1 212 339 0687 Fax: + 1 212 755 6052 Email: khallman@popcouncil.org Citation: Hallman, Kelly. 2007 . "Nonconsensual sex, school enrollment and educational outcomes in South Africa," Africa Insight 37(3): 454-472.
  • 2. Nonconsensual Sex, School Enrollment and Educational Outcomes in South Africa Abstract Sexual violence is a significant problem in South Africa. Such encounters bring psychological trauma, social stigma, and the risk of pregnancy, HIV and STIs. Existing qualitative research indicates that survivors have difficulty concentrating on school-work, with many reportedly losing interest and some leaving school. The relationship between these experiences and school enrollment and educational attainment has not been quantified in sub-Saharan Africa. Using a random sample of 14-24-year-olds in KwaZulu-Natal, South Africa, I find the experience of nonconsensual sex to be associated with significantly lower chances of current school enrollment among males and females, and lower educational attainment and more school delays among females. Multivariate results show a significant negative relationship between nonconsensual sexual experience and schooling progression amongst females. Biographical Statement Kelly Hallman is an Associate at the Population Council. Her current research investigates factors that promote safe and productive transitions to adulthood, and how policies and programmes can enhance the decision-making power of young people—especially girls—with regard to their sexual and reproductive health, education, work, and marriage choices. Before joining the Population Council in 2001, Dr. Hallman was a Research Fellow at the International Food Policy Research Institute where she focused on how gender and intrahousehold power dynamics affect food and nutrition security in developing countries. She received her Ph.D. in economics from Michigan State University. Acknowledgements This document is an output from a project funded by the UK Department for International Development (DfID) for the benefit of developing countries. The views expressed are not necessarily those of DfID.
  • 3. Introduction Reports demonstrate that sexual violence is a significant problem in South Africa. South Africa Police Service statistics indicate that from April 2003 to March 2004, 52,733 rapes and attempted rapes were reported, and it is believed that this figure underestimates the true extent of rape due to high levels of underreporting.1 Rates per 10,000 women are among the highest in the world.2 A 2001 Human Rights Watch (HRW) report3 described social and sexual violence to be common in schools. This report took South Africans off guard. In response to the findings, UNICEF commissioned the Human Sciences Research Council (HSRC) to study the issue: Qualitative results from the study, of eight schools across South Africa, indicated that the prevalence of sexual violence varies considerably, being virtually non-existent in some schools and pervasive in others.4 South African studies of learners’ experiences of sexual violence, both within and outside of school, have been undertaken. The Medical Research Council study of learners in grades 8-115 found that 12.9 and 14.4 percent of male and female learners, respectively, had been physically assaulted by a boyfriend or girlfriend, and that 11.1 percent of females and 8.1 percent of males had been forced to have sex. The CIET (Centro de Investigación de Enfermedades Tropicales)6 study showed that 8.6 percent of learners aged 11-19 had been forced to have sex without their consent. Various community- level studies also indicate that sexual violence is a fact of life for many young people in South Africa.7,8,9,10,11,12,13 Besides the psychological trauma and social stigma these encounters bring, the potential health risks of pregnancy, HIV and other STIs may be large since a condom is seldom used.14,15,16 Interviews with girls17 also indicate that school-aged rape survivors found it harder to concentrate on their studies after the assault; some lost interest in school, transferred schools, or left school altogether. While these findings are very important, the relationship between such experiences and progression through school 2
  • 4. and educational attainment has not been well-studied in South Africa or elsewhere, amongst either female or male learners. To examine these issues, analyses is undertaken of the Transitions to Adulthood in the Context of AIDS18 survey of 4,100 young women and men aged 14–24 years residing in KwaZulu-Natal in 2001. The data include a wide variety of information about the lives of young people living in a setting characterized by high reported rates of social and sexual violence, HIV, poverty and inequality. For all respondents, there is both a complete educational history and questions answered about experiences of sexual violence. A better understanding of the relationships between experiences of sexual violence and schooling status for girls and boys may elucidate a potentially important contributing factor to slow school advancement in South Africa, as well as point to areas of potential program and policy intervention. Sexual Violence and Human Capital Accumulation The United Nations Declaration on the Elimination of Violence Against Women19 broadly defines gender-based violence as “any act that results in or is likely to result in physical, sexual, or psychological harm or suffering to women, including threats of such acts, coercion or arbitrary deprivation of liberty, whether in public or private life.” The World Report on Violence and Health20 defines sexual violence as “any sexual act, attempt to obtain a sexual act, unwanted sexual comments or advances, or acts to traffic, or otherwise directed, against a person’s sexuality using coercion, by any person regardless of their relationship to the victim, in any setting, including but not limited to home and work.” An Inter-American Development Bank (IDB) study21 defines domestic violence as “violence that takes place between people related to each other by blood, marriage or common law, versus social violence, which occurs between individuals not so related.”22 The operational definition used in the current study is described in the “Data and Methods” section of the paper. 3
  • 5. In reviewing literature on the effects of violence in six countries in Latin America (Brazil, Colombia, El Salvador, Mexico, Peru and Venezuela), Buvinic et al.23 classify the socio-economic costs of social and domestic violence into four categories. (1) Direct costs—The value of goods and services used in treating or preventing violence. These include medical and counseling services, police and criminal justice system expenditures, and social services such as domestic violence prevention and education, advocacy programs, alternative housing for victims, and training for police, doctors and others. (2) Non-monetary costs—which are morbidity and mortality effects of violence. This category includes health impacts that do not necessarily result in demand for health services, such as increased morbidity, abuse of alcohol and drugs, and depressive disorders, as well as increased mortality through homicide and suicide. (3) Economic multiplier costs—include macroeconomic, labor market, and inter-generational productivity effects of violence. In this grouping are lower rates of school or labor market participation, decreased accumulation of human capital, reduced productivity at school or on the job, increased absenteeism, lower earnings, negative inter-generational productivity impacts, and lower levels of saving and investment at the macroeconomic level. (4) Social multiplier—costs which impact on inter-personal relations and quality of life. These effects comprise the erosion of social capital due to the social isolation of victims, and the intergenerational transmission of the perpetration and acceptance of violent behaviors, as well as unhealthy parenting and interpersonal behaviors. The current study focuses on the category Buvinic and colleagues refer to as “economic multiplier” effects. Evidence on the intergenerational aspects of this effect is most plentiful in Latin America. Children who witness domestic violence at home or have been abused themselves are reported to have greater difficulty at school in the form of disciplinary problems, and a greater likelihood of repeating grades and dropping out of school earlier.24 In Chile, children who reported suffering serious abuse did significantly worse in school than children who reported no physical abuse.25 Such children experience difficulty in developing close and positive friendships.26 These 4
  • 6. effects suggest a direct impact on children’s human and social capital and their future ability to effectively compete in the labor and marriage markets.27 Apart from the loss of human and social capital, there are direct costs to school systems as children from violent homes may perform poorly and have to repeat grades. Another aspect of the economic multiplier effects of violence includes “missed education”, that is, holding children (mostly girls) out of school with the intention of reducing their exposure to potential perpetrators (often boys and educators) in the belief that this will reduce their risk.28 29 Despite parents’ good intentions, Jejeebhoy and Bott’s review30 indicates that sexual violence and harassment are common even in settings where parents strictly limit girls’ interaction with boys, and that these restrictions may in fact compound girls’ risks. In these situations boys and men have been observed, in India for example, to use the threat of ruining a girl’s reputation as a way of pressuring her into having sex or keeping quiet about an incident of sexual abuse or harassment.31 A third type of economic multiplier effect is the direct effect on victims themselves. In 1993 the World Bank estimated that in industrialized countries, sexual assault and violence accounted for nearly one in five healthy life years lost among women aged 15-44.32 Women faced with violence are less able to participate fully in the various realms of their lives. Sexual and domestic violence are associated with lower success in obtaining, performing in, and keeping a job, and with less financial independence and security.33,34,35,36 The effects of violence are also associated with direct and indirect costs to the workplace, such as decreased productivity, increased health care costs, absenteeism, errors, and time spent coping with problems.37 While there is in fact little evidence of the direct effects of sexual violence on school attendance and educational attainment in developing countries, a USAID-sponsored review of literature on school-related gender-based violence38 found three studies (in addition to the HRW report for South Africa)39 that provide some information. One study in Botswana40 indicated that at least 11 5
  • 7. percent of schoolgirls were seriously considering dropping out of school because of ongoing harassment by teachers. A report by Hallam41 indicates that sexual harassment and violence were causing girls in sub-Saharan Africa to drop out of school. A small study in Ethiopia42 found that school-related gender-based violence was cited as a factor in both low enrollment and school dropout for girls. Sexual Violence and Education in South Africa Several studies point to the magnitude of sexual violence among young people in South Africa. A study of sexually-active urban adolescents in KwaZulu-Natal revealed that 55 percent of female respondents reported having attempted to refuse sexual advances from their most recent partner; 71 percent of these respondents admitted their attempts to avoid sex had not been successful and that their refusal nearly always resulted in physical coercion, abuse, or threats of rejection.43 Research by Wood and Jewkes44 revealed that 60 percent of young women in a South African township have had sex against their wishes, and many viewed sexual coercion as a routine part of a relationship. Other studies in South Africa reported that young women’s attempts to discuss condoms or HIV/AIDS before a sexual encounter could lead to violence or rape.45,46 In the 1998 South Africa Demographic and Health Survey, 12 percent of 15–19-year-old women and 14 percent of 20–24-year-old women reported they had been abused by a partner at some point in their lives;47 5 percent of 15-19- and 20-24-year-olds reported having been raped.48 Among those women who had been raped before the age of 15 years, one-third named their school teacher as the rapist.49 The South Africa Department of Education50 cites alcohol and drugs on school premises, as well as violence perpetrated by a subset of male educators, as contributing to sexual violence within the school setting. While school enrollment is high in South Africa,51 school delays and slow progression through school is a significant problem.52,53 Adolescent child-bearing is also high54 and teenage pregnancy has 6
  • 8. been found to be associated with school delays among girls.55,56 There are few quantitative empirical studies that have documented the relationship between the experience of sexual violence and schooling for individual young people in South Africa. Data and Methodology The Transitions57 data offer an opportunity to explore the relationships between coerced sexual experiences, school enrollment, and educational attainment. Two districts in KwaZulu-Natal province were purposively chosen for the study site - Durban Metro and Mtunzini Magisterial District, as they represent urban, peri-urban and rural areas of the province. A modified stratified, multi-stage cluster sampling method was used,58 with enumeration areas from the 1996 census serving as the primary sampling unit. Interviews were conducted with all willing 14–24 year-olds residing in each household of each sample enumeration area. Informed consent was sought from all participants and from the guardians of minor age participants. Ethical clearance for the study protocol was granted by the Institutional Review Board of the Population Council. Many aspects of transitions to adulthood were covered in the survey, including schooling, paid and unpaid work, sexual and reproductive health behavior, HIV/AIDS knowledge and attitudes, childbearing, marriage, and perceptions of social connectedness and safety. The study also includes interviews with heads of households of youth, mainly parents, about household composition, living conditions, economic status, and HIV/AIDS issues, as well as interviews with secondary school principals to assess the extent of coverage of the school-based life-skills curriculum and its impact on youth HIV knowledge, attitudes, and sexual risk-taking behaviors. Sexual behaviors and experiences were collected using verbal face-to-face interviews by local field staff of the same race, gender, and general age as the respondent. The sensitive nature of many of the questions required that the interviews be conducted with in private. Interviewees were asked 7
  • 9. whether they were willing, persuaded, tricked, forced, or raped at their first sexual encounter.59 Respondents were also asked if they have ever had sexual intercourse when somebody was physically forcing, hurting, or threatening them. If the answer to this question was “no”, a follow-up question was asked about whether s/he had ever tried to refuse sex but had not been successful. For the analysis, a variable indicating experience of any nonconsensual sex was constructed, defined as being tricked, forced, or raped at first sex, or an affirmative response to either the physically forced sex question or the follow-up question for ever unsuccessfully attempting to refuse sex. Information is not available on where these incidents took place or who the perpetrator was; it is therefore not possible to link reported nonconsensual sexual experiences directly with the school setting. Brookes and Higson-Smith’s60 study, however, indicates that girls in secondary school (grades 8-12) are at risk of rape both in school and in their community. Jejeebhoy and Bott61 found that many of the forced sexual experiences of young women globally are by someone the girl was already acquainted with and in a familiar setting, such as the home or school. With regard to schooling and educational attainment, for each year after entering primary school the survey respondent reported whether s/he was enrolled that year, and whether the school year was completed successfully or not. For each instance of withdrawal for all or part of a school year, the reason was solicited. Since the majority of young people in South Africa have experienced some form of schooling delay, this level of detail provides a unique opportunity to track a respondent’s educational progress. Using these data, Hallman and Grant62 reported that gender is an important determinant of the timing of school delays. Although girls advance more quickly than boys through primary school, their performance begins to falter at the secondary level. At age 14-15, 45 percent of males versus 35 percent of females have had school delay.63 By age 20-22, 56 percent of males and 57 percent of females have experienced at least one school delay. Among young people who have had a delay, the major set of factors reported is economic constraints. Lack of interest and poor performance 8
  • 10. is also cited by both girls and boys. Among females, a considerable percentage who have had delays report them as being pregnancy-related. While the effects of trauma from sexual violence was not available as a choice in the survey as a cause of delay, this may in fact underlie some of the delays which are reported as due to lack of interest/poor performance and pregnancy-related causes. Educational histories, combined with the data on nonconsensual sexual experiences allow for an exploration of the relationship between sexual violence, school enrollment, and educational outcomes. Except for the first sexual experience, the survey did not collect information on when nonconsensual encounters occurred. The sequencing of nonconsensual sex and various schooling events is therefore unknown. For the multivariate analysis we thus utilize a bivariate probit estimator64 to test statistically for joint nature of experience of nonconsensual sex (0-1) and current school enrollment/attainment of matric (0-1) among 14-19-year-olds, and having experienced nonconsensual sex (0-1) and having attained a matriculation certificate (0-1) among 20-24 year-olds.65 A third model is also estimated for the entire sample where the schooling outcome is defined as either currently enrolled in school or has completed secondary school. Outcomes are modeled as a function of underlying exogenous individual (age and population group [race]) and household characteristics (household wealth, household size, highest level of adult education in the household, and parental residence and survival) and urban versus rural residence. The data are weighted for unequal sampling probabilities and standard errors are adjusted for cluster sampling. The statistical package STATA was used for all data preparation and analysis. Bivariate Results The reported prevalence of nonconsensual sex among 14-24-year-olds is 26 percent among females and 7 percent among males. Among 14-19-year-olds, the levels are 19 and 5 percent, respectively, and among 20-24-year-olds, 40 and 11 percent, for females and males, respectively. 9
  • 11. Table 1 presents school enrollment and educational attainment by history of sexual experience. Both girls and boys aged 14-19 with sexual experience have statistically lower school enrollment rates and are more likely to have had a school delay; differences by sexual debut status are much larger for girls than boys. Girls and boys in this age group who have experienced nonconsensual sex are significantly less likely to be enrolled in school or have matric66, with differences being much larger for females. School delays are also more likely among those affected, but the difference is significant only for females. To gain further insight into whether sexual experience itself or a nonconsensual sexual encounter affects education, outcomes are presented by nonconsensual sex conditional upon having had a sexual experience. Among those who have had sex, school enrollment is much lower for girls than boys (largely related to pregnancy risk, as described below). Within the group who has had sex, girls and boys who have experienced nonconsensual sex are less likely to be enrolled in school. Among 20-24-year-olds, females who have had sex have significantly lower grade attainment, lower rates of completing matric, and a higher prevalence of school delays. Males reported lower rates of completing matric and more school delays. Females who have had nonconsensual sex have poorer outcomes across the board. Conditioning on any sexual experience, completion of matric is lower and school delays are greater among female victims of nonconsensual sexual experiences. Among males, victims of nonconsensual sex have slightly lower matric rates but the difference between the two groups is not statistically significant. 10
  • 12. TABLE 1. SCHOOL ENROLLMENT/EDUCATIONAL ATTAINMENT BY EVER HAD SEX AND ……………..EVER EXPERIENCED NONCONSENSUAL SEX Age 14-19 Age 20-24 Enrolled or Ever had a N Grade Has Ever had a N Has Matric School Attainment Matric School Delay Delay FEMALES Ever had sex = No 95% 35% 942 11.5 70% 33% 111 Ever had sex = Yes 61% 52% 547 10.5 36% 61% 572 Means test (p-value) 0.00 0.00 0.00 0.00 0.00 Nonconsensual sex = No 89% 38% 1203 10.8 49% 50% 415 Nonconsensual sex = Yes 57% 57% 286 10.4 29% 67% 273 Means test (p-value) 0.00 0.00 0.00 0.00 0.00 Ever had sex = Yes & 66% 49% 261 10.6 42% 55% 304 Nonconsensual sex = No Ever had sex = Yes & 57% 56% 286 10.4 29% 67% 273 Nonconsensual sex = Yes Means test (p-value) 0.05 0.12 0.15 0.00 0.00 MALES Ever had sex = No 94% 43% 638 10.5 55% 44% 75 Ever had sex = Yes 81% 56% 698 10.5 41% 59% 550 Means test (p-value) 0.00 0.00 0.98 0.03 0.01 Nonconsensual sex = No 89% 49% 1273 10.5 44% 57% 560 Nonconsensual sex = Yes 73% 55% 63 10.5 38% 59% 66 Means test (p-value) 0.00 0.39 0.98 0.37 0.72 Ever had sex = Yes & 82% 56% 575 10.5 42% 59% 482 Nonconsensual sex = No Ever had sex = Yes & 73% 55% 62 10.5 38% 59% 66 Nonconsensual sex = Yes Means test (p-value) 0.07 0.81 0.93 0.53 0.97 The correlations between nonconsensual sex, pregnancy risk, and age at sexual initiation are also of interest for females. Table 2 indicates that females who have ever experienced nonconsensual sex are more likely to have been pregnant and to have had an earlier sexual debut. 11
  • 13. TABLE 2. EVER PREGNANT AND AGE AT FIRST SEX BY NONCONSENSUAL SEX Nonconsensual Nonconsensual N Means Sex=No Sex=Yes Test (p- value) All females Ever pregnant (age 14-19) 9% 45% 1489 0.00 Ever pregnant (age 20-24) 46% 71% 688 0.00 Conditional on ever had sex Ever pregnant (age 14-19) 42% 45% 547 0.49 Ever pregnant (age 20-24) 63% 71% 577 0.06 Age at first sex (age 14-24) 16.8 16.2 1118 0.00 In sum, the bivariate findings indicate a significant relationship between experiencing sexual violence and (a) lower rates of school enrollment for girls and boys, and (b) lower educational attainment for girls. Multivariate Results Bivariate probit estimates of the joint outcomes “currently enrolled in school (or completed matric)” and “ever experienced nonconsensual sex” for females aged 14-19 years are presented in Table 3. The low prevalence of nonconsensual sex among males this age resulted in an unstable statistical model that did not yield interpretable results. An examination of the determinants of each outcome reveals that being older, residing in a household with poorly educated adults, and being poor are the primary determinants of girls not being enrolled in school. Girls who are older are more likely to have experienced nonconsensual sex. Relative to African females, Coloured and Indian females are significantly less likely to have experienced nonconsensual sex, as are girls who reside in households with better educated adult members. Females in the lowest wealth quintile are also more likely to have experienced nonconsensual sex. Parental residence and survival do not appear to significantly affect either outcome. The Wald test of rho equals zero indicates that the null hypothesis of the two outcomes 12
  • 14. being independent can in fact be rejected, implying a significant statistical relationship between the two outcomes. In Table 4 the bivariate probit estimates of the joint outcomes “has a secondary matriculation certificate” and “ever experienced nonconsensual sex” for 20-24-year-old females and males are shown. Among females, being older and Indian increase the chances of completing matric, while residing in a poor household, with many members, or with adults who are poorly-educated reduces the likelihood of completing secondary school. Experience of nonconsensual sex among females this age appears to be influenced by race and household structure and size. Indians and Whites participants have significantly lower chances of experiencing nonconsensual sex than Africans, while those residing in households with many members have greater chances, as do those who do not reside with their living biological fathers. The Wald test of rho equals zero indicates that the null hypothesis of the outcomes being independent cannot be rejected for either sex, implying no significant statistical relationship between nonconsensual sex and attainment of matric. For 20-24-year-old males, being older, Indian, or White increases the chances of having completed matric, while residing in a poor household or with poorly-educated adults reduces the chances. As with females, the likelihood of nonconsensual sex is affected by race and household demographic factors. Coloured males have significantly lower chances of being subjected to nonconsensual sex than African males. Similar to young women, young men who do not reside with their living biological father are at increased risk. Urban males are at greater risk for nonconsensual sexual than rural males. Joint estimates of the pooled education outcome (either “currently attending school below the secondary level” or “has a secondary matriculation certificate”) and nonconsensual sex for 14-24-year- olds are shown in Table 5. For this model, the null hypothesis of the outcomes being independent can be rejected for females but not males, indicating a significant statistical relationship between 13
  • 15. nonconsensual sex and education for females only. Young people in poor households and whose adult members have little education are less likely to be enrolled or have a matric (e.g., are more likely to be school dropouts). For females, not residing with their living biological father significantly reduces educational prospects, while being a maternal orphan is detrimental for the education of boys. For females and males, the risk of nonconsensual sex rises with age and is more likely for African youths. Among females, residing in a poor household also increases risk of nonconsensual sex. For males, not residing with a living mother appears to reduce the risk, while not residing with a living father increases it. Discussion This study examines the relationships between young people’s experience of nonconsensual sex and their schooling status. While it is not possible, given the nature of the available data, to directly attribute poor schooling outcomes to nonconsensual sexual experiences, the results do confirm that sexual violence is significantly related to lower school enrollment and educational attainment, especially for females. Bivariate results show that young women and men who have ever had a nonconsensual sexual encounter are less likely to be enrolled in school. Young women (but not men) who have had such experiences are significantly more likely to have had a school delay and to have lower educational attainment. The multivariate results confirm the statistical relationship between a nonconsensual sex experience and poorer schooling outcomes among females. Progression through school for both girls and boys is inhibited by belonging to a traditionally disadvantaged racial group (African), living in a poor or crowded household, co-residence with poorly- educated adults, and not residing with living parents. For females but not males, belonging to a household in the lowest wealth quintile of the sample also raises the risk of experiencing nonconsensual sex. Urban residence increases the risks for males. 14
  • 16. Most South African studies of this topic do not discuss race as a determinant, so it is not possible to compare the race results with previous studies of nonconsensual sex. Poverty has been shown in a several international studies to increase the risk of nonconsensual sex for girls and boys.67 A South African study68 found that violence in the sexual relationships of secondary school students is more common among those who are economically disadvantaged. Using the Transitions data, Hallman69 reported that females from poorer households are the least likely to report that their first sex experience was a willing encounter. Violence en route to school and within and around the school grounds is also believed to put poorer schoolgirls at higher risk, since they are least able to afford safe transport, and many live in dangerous neighbourhoods and attend low-resourced, unsafe schools.70,71 The relationship between parental co-residence and support, and protection from sexual violence, is not well-studied72 but has been documented for girls in China73 and India.74 A Human Rights Watch75 study in Zambia suggests that parental absence is a substantial risk factor for nonconsensual sex for girls. Girls who had lost their parents were reported to be particularly vulnerable to rape by family members who provided shelter. Conclusion The ability to live free from the fear of violence is a basic human right. Sexual violence is a public health problem because it leads to increased morbidity and mortality; it is also, however, a potentially serious obstacle to economic development. While a number of studies have estimated the morbidity and mortality effects of sexual violence, fewer have dealt with its impacts on economic development. Among those that have, the focus is often on time and productivity losses in the workplace. Only a handful have examined the relationships between sexual violence and school attendance and educational attainment, and these studies frequently focus only on the intergenerational aspects of domestic violence on children’s schooling. One possible reason for the lack of evidence on 15
  • 17. this topic is that in many low-resource settings girls historically drop out of school around the time of puberty.76 With school attendance rates of adolescent girls on the rise in developing countries, however, the relationship between the experience of sexual violence and school attendance and educational attainment is pertinent in an increasing number of settings. Recent studies of gender-based violence confirm that school-aged young people are victims of violence (Jejeebhoy and Bott 2003).77 The high secondary enrollment rates and the prevalence of reported sexual violence in South Africa make it an appropriate setting in which to examine this important issue. Education is key to attaining decent employment and a reasonable quality of life in a globalizing world. A better understanding of the causes of sexual violence and its relationship to the schooling experiences of young people is crucial to enhancing the well-being of future generations. 16
  • 18. 17
  • 19. TABLE 3. BIVARIATE PROBIT: CURRENTLY ENROLLED (OR HAS MATRIC) AND EVER …………….EXPERIENCED NONCONSENSUAL SEX (FEMALES AGED 14-19 YEAR OF AGE) Enrolled (or has matric) Nonconsensual Sex Coef. SE p- Coef. SE p- value value Age (years) -0.23 0.05 0.00 0.17 0.05 0.00 Colored (v. African) 6.73 0.31 0.00 -0.88 0.35 0.01 Asian (v. African) -0.17 0.27 0.53 -0.96 0.39 0.01 White (v. African) -0.30 0.48 0.53 -0.49 0.38 0.20 Low wealth (vs. high wealth) -1.37 0.25 0.00 0.70 0.26 0.01 Low-mid wealth (vs. high wealth) -1.04 0.25 0.00 0.19 0.29 0.52 Mid wealth (vs. high wealth) -0.45 0.23 0.05 0.02 0.25 0.94 High-mid wealth (vs. high wealth) -0.66 0.21 0.00 0.18 0.23 0.44 Household size 0.00 0.02 0.85 -0.01 0.02 0.51 HH primary or less educ (v. post-secondary) -0.99 0.48 0.04 0.74 0.32 0.02 HH some secondary educ (v. post-secondary) -0.79 0.47 0.09 0.51 0.32 0.11 HH education secondary, no matric (v. post- -0.62 0.48 0.19 0.65 0.41 0.12 secondary) HH education matric secondary (v. post-secondary) -0.51 0.53 0.34 0.49 0.33 0.14 Mother alive, not resident (v. resident) 0.07 0.17 0.69 0.10 0.17 0.55 Mother dead (v. resident) -0.06 0.21 0.78 0.16 0.18 0.36 Father alive, not resident (v. resident) -0.23 0.19 0.22 0.08 0.17 0.65 Father dead (v. resident) -0.20 0.21 0.34 0.15 0.20 0.47 Urban (v. rural) 0.05 0.14 0.72 0.14 0.14 0.32 Constant 6.70 1.09 0.00 -4.46 0.93 0.00 athrho -0.48 0.12 0.00 rho -0.45 0.09 Wald test of rho=0: Prob>chi2 = 0.0000 Number of obs 1427 Wald chi2 2182.17 Prob > chi2 0.000 18
  • 20. TABLE 4. BIVARIATE PROBIT: HAS MATRIC AND EVER EXPERIENCED NONCONSENSUAL SEX (20-24-year-olds) FEMALES MALES Has Matric Nonconsensual Sex Has Matric Nonconsensual Sex Coef. SE p-value Coef. SE p- Coef. SE p- Coef. SE p- value value value Age (years) 0.21 0.06 0.00 0.05 0.06 0.45 0.16 0.06 0.02 0.05 0.08 0.52 Colored (v. African) 0.23 0.55 0.67 -0.52 0.55 0.35 0.77 0.45 0.09 -6.35 0.31 0.00 Asian (v. African) 1.06 0.25 0.00 -2.34 0.32 0.00 0.96 0.23 0.00 -0.44 0.34 0.20 White (v. African) 0.59 0.48 0.23 -1.06 0.51 0.04 1.46 0.37 0.00 -0.23 0.60 0.70 Low wealth (vs. high wealth) -1.08 0.28 0.00 0.19 0.32 0.55 -1.06 0.31 0.00 0.51 0.55 0.35 Low-mid wealth (vs. high wealth) -0.31 0.27 0.25 -0.01 0.33 0.98 -0.39 0.31 0.20 0.37 0.50 0.46 Mid wealth (vs. high wealth) -0.13 0.25 0.61 0.04 0.34 0.90 0.02 0.28 0.94 0.28 0.44 0.53 High-mid wealth (vs. high wealth) -0.07 0.24 0.76 0.11 0.31 0.72 -0.26 0.26 0.32 0.55 0.40 0.17 Household size -0.09 0.02 0.00 0.05 0.02 0.04 -0.03 0.03 0.23 0.05 0.03 0.11 HH primary or less educ (v. post- -1.82 0.64 0.01 -0.53 0.50 0.29 -1.14 0.44 0.01 -0.20 0.64 0.75 secondary) HH some secondary educ (v. post- -1.73 0.65 0.01 -0.14 0.49 0.77 -0.94 0.42 0.03 0.27 0.62 0.66 secondary) HH education secondary, no matric -1.13 0.70 0.11 -0.77 0.56 0.17 -0.29 0.45 0.52 -0.53 0.63 0.40 (v. post-secondary) HH education matric secondary (v. -0.86 0.70 0.22 -0.41 0.53 0.45 -0.64 0.47 0.17 0.32 0.62 0.60 post-secondary) Mother alive, not resident (v. resident) -0.13 0.18 0.48 -0.03 0.20 0.89 0.18 0.20 0.38 -0.42 0.26 0.10 Mother dead (v. resident) 0.16 0.29 0.59 -0.19 0.30 0.53 0.03 0.24 0.90 0.07 0.28 0.79 Father alive, not resident (v. resident) -0.21 0.19 0.26 0.43 0.19 0.03 -0.31 0.20 0.13 0.69 0.28 0.01 Father dead (v. resident) -0.22 0.21 0.28 0.34 0.20 0.09 -0.06 0.20 0.75 0.50 0.31 0.11 Urban (v. rural) 0.20 0.19 0.31 0.02 0.17 0.92 -0.05 0.20 0.81 0.53 0.22 0.02 Constant -2.41 1.36 0.08 -1.30 1.36 0.34 -2.19 1.41 0.12 -3.73 1.79 0.04 athrho -0.09 0.10 0.34 0.10 0.12 0.42 rho -0.09 0.10 0.10 0.12 Wald test of rho=0 Prob>chi2 = 0.3413 Prob > chi2 = 0.4181 Number of obs 676 590 Wald chi2 211.03 2124.82 Prob > chi2 0.000 0.000
  • 21. TABLE 5. BIVARIATE PROBIT: ENROLLED OR HAS MATRIC AND EVER EXPERIENCED NONCONSENSUAL SEX (14-24-year-olds) FEMALES MALES Has Matric Nonconsensual Sex Has Matric Nonconsensual Sex Coef. SE p-value Coef. SE p- Coef. SE p- Coef. SE p- value value value Age (years) -0.17 0.02 0.00 0.12 0.02 0.00 -0.18 0.02 0.00 0.11 0.02 0.00 Colored (v. African) 0.67 0.34 0.05 -0.82 0.28 0.00 -0.55 0.39 0.17 -6.08 0.25 0.00 Asian (v. African) -0.02 0.20 0.93 -1.16 0.36 0.00 -0.27 0.27 0.32 -0.73 0.22 0.00 White (v. African) -0.01 0.45 0.98 -0.63 0.31 0.05 -0.70 0.48 0.15 -0.45 0.42 0.29 Low wealth (vs. high wealth) -1.15 0.20 0.00 0.52 0.21 0.01 -0.87 0.25 0.00 0.33 0.32 0.30 Low-mid wealth (vs. high wealth) -0.81 0.21 0.00 0.10 0.23 0.66 -0.71 0.26 0.01 0.11 0.31 0.71 Mid wealth (vs. high wealth) -0.25 0.20 0.22 0.04 0.20 0.85 0.05 0.24 0.85 0.29 0.27 0.29 High-mid wealth (vs. high wealth) -0.43 0.18 0.02 0.14 0.19 0.47 -0.13 0.22 0.55 0.21 0.25 0.40 Household size -0.01 0.02 0.39 0.01 0.02 0.47 -0.04 0.02 0.03 -0.01 0.02 0.60 HH primary or less educ (v. post- -1.39 0.48 0.00 0.29 0.28 0.29 -1.86 0.55 0.00 -0.05 0.39 0.89 secondary) HH some secondary educ (v. post- -1.27 0.48 0.01 0.24 0.27 0.38 -1.70 0.54 0.00 0.20 0.38 0.59 secondary) HH education secondary, no matric (v. -0.91 0.50 0.07 0.14 0.35 0.69 -1.42 0.64 0.03 -0.13 0.37 0.72 post-secondary) HH education matric secondary (v. -0.88 0.52 0.09 0.15 0.29 0.62 -0.94 0.58 0.10 -0.02 0.39 0.95 post-secondary) Mother alive, not resident (v. resident) 0.04 0.13 0.73 0.03 0.14 0.86 -0.13 0.16 0.42 -0.46 0.17 0.01 Mother dead (v. resident) 0.08 0.18 0.66 0.01 0.16 0.95 -0.73 0.20 0.00 -0.13 0.20 0.53 Father alive, not resident (v. resident) -0.27 0.14 0.05 0.18 0.14 0.21 -0.10 0.14 0.48 0.35 0.18 0.05 Father dead (v. resident) -0.20 0.14 0.16 0.21 0.15 0.17 -0.17 0.17 0.32 0.32 0.19 0.09 Urban (v. rural) 0.00 0.11 0.99 0.14 0.12 0.23 -0.40 0.14 0.01 0.18 0.16 0.24 Constant 5.99 0.65 0.00 -3.33 0.48 0.00 6.98 0.72 0.00 -3.77 0.71 0.00 Athrho -0.32 0.08 0.00 -0.04 0.10 0.71 rho -0.31 0.07 -0.04 0.10 Wald test of rho=0 Prob>chi2 = 0.0000 Prob>chi2 = 0.7058 Number of obs 2103 1844 Wald chi2 304.53 1568.3 1 Prob > chi2 0.000 0.000 20
  • 22. Notes and References 1 South African Police Service, Crime statistics as released in 2004, http://www.saps.gov.za/statistics/reports/crime stats/2004/_pdf/crimes/Rape.pdf, February 2005. 2 Health Systems Trust, South African Health Review 2000, Durban, South Africa, 2000. 3 Human Rights Watch, Scared at school: Sexual violence against girls in South African schools, 2001, http://www.hrw.org/reports/2001/safrica/ 4 H Brookes and Higson-Smith, ‘Responses to gender violence in schools’, in L Richter, A Dawes, and Higson- Smith (eds), Sexual Abuse of Young Children in Southern Africa, Cape Town: HSRC Press, 2004. 5 S P Reddy, S Panday, D Swart, C C Jinabhai, et al., Umthenthe Uhlaba Usamila – The South African Youth Risk Behaviour Survey 2002, Cape Town: South African Medical Research Council, 2003 6 N Andersson, A Ho-Foster, J Matthis, N Marokoane, et al., ‘National cross sectional study of views on sexual violence and risk of HIV infection and AIDS among South African school pupils’, British Medical Journal, 329, 952-955, 2004. 7 Ibid. 8 G Buga, DAmoko and D Ncaylyana, ‘Sexual behaviour, contraceptive practice and reproductive health among school adolescents in rural Transkei,’ South African Medical Journal, 86, 523–552, 1996. 9 C Varga, and L. Makubalo, 1996, ‘Sexual non-negotiation’, Agenda, 28, 31–38. 10 C A Varga, ‘Sexual decision-making and negotiation in the midst of AIDS: Youth in KwaZulu-Natal, South Africa’, Health Transition Review 2, Supplement 3, 45–67, 1997. 11 K Wood, and R Jewkes, ‘Violence, rape, and sexual coercion: Everyday love in a South African township’, Gender and Development, 5(2), 41–46, 1997. 12 C MacPhail, and C Campbell, ‘I think condoms are good but, aai, I hate those things’: Condom use among adolescents and young people in a southern African township’, Social Science and Medicine, 52, 2001, pp. 1613– 1627. 13 C Campbell, Letting them die: Why HIV/AIDS Prevention Programmes Fail, Oxford: James Currey, 2003. 14 S Maman, J K Mbwambo, N M Hogan et al., ‘HIV-positive women report more lifetime partner violence: Findings from a voluntary counseling and testing clinic in Dar es Salaam, Tanzania’, American Journal of Public Health, 92(8), 1331-1337, 2002. 15 A van der Straten, R King, O Grinstead et al., ‘Sexual coercion, physical violence and HIV infection among women in steady relationships in Kigali’, Rwanda. AIDS and Behavior, 2(1), 61-73, 1998. 16 K L Dunkle, R K Jewkes, H C Brown et al., ‘Gender-based violence, relationship power, and risk of HIV infection in women attending antenatal clinics in South Africa’, The Lancet, 363(9419), 1415-142.1, 2004. 17 Human Rights Watch 2001 18 R Magnani, K MacIntyre, A M Karim, L P Hutchinson, and the Transitions Study Team, C Kaufman, N Rutenburg, K Hallman, J May, and A Dallimore. ‘The impact of life skills education on adolescent sexual risk behaviors in KwaZulu-Natal, South Africa’, Journal of Adolescent Health, 36, 289-304, 2005. 21
  • 23. 19 United Nations, Economic and Social Council, Towards an Effective Implementation of International Norms to End Violence against Women, Report of the Special Rapporteur on violence against women, its causes and consequences, E/CN.4/2004/66, December 26, 2003, p. 15. United Nations, Economic and Social Council. 20 World Health Organisation (WHO), World Report on Violence and Health, Geneva: WHO, 2002. 21 M Buvinic, A R Morrison and M Shifter, ‘Violence in the Americas: A framework for action’, in Too Close to Home: Domestic Violence in the Americas, A R Morrison, M Buvinic, and M L Biehl (eds). Washington DC: Inter- American Development Bank, 1999. 22 Still other categories of violence include “economic abuse” and “structural violence.” The 1998 South Africa Demographic and Health survey 77 defines economic abuse as an intimate partner regularly not providing money for food, rent, or bills while having money for other things; Rasool et al.78 also include intimate partner taking money without consent. Structural violence is defined loosely as the negative effects of poverty and inequality in access to goods, services, opportunities, and basic human rights. While the influences of poverty on sexual violence and schooling are addressed here, economic abuse and structural violence per se are not discussed directly. 23 M Buvinic, A R Morrison and M Shifter 1999. 24 A R Morrison, and M B Orlando, 1999, ‘Social and economic costs of domestic violence: Chile and Nicaragua’ in R. Morrison, M. L. Biehl, M. Buvinic and L. Biehl (eds), Too Close to Home: Domestic Violence in Latin America, Baltimore: John Hopkins University. 25 S. Larrain, ‘Violencia Doméstica Contra la Mujer en América Latina y el Caribe; Revisión de Décadas de Acción’, Documento de la Conferencia: Violencia Doméstica en América Latina y el Caribe: Costos, Programas y Políticas. Banco Inter-Americano de Desarrollo, Washington, D.C., 20- 21 de octubre., 1977, quoted in M Buvinic, A R Morrison and M Shifter, ‘Violence in the Americas: A framework for action’, in Too Close to Home: Domestic Violence in the Americas, A R Morrison, M Buvinic, and M L Biehl (eds). Washington DC: Inter-American Development Bank, 1999. 26 UNICEF, Domestic Violence Against Women and Girls. Innocenti Digest No. 6, June, 2000, Florence, Italy. UNICEF. Innocenti Centre, 2000. 27 M Buvinic, A R Morrison and M Shifter 1999. 28 J Omale, ‘Tested to their limit: Sexual harassment in schools and educational institutions in Kenya’, in J Mirsky and M Radlett (eds), No Paradise Yet: The World’s Women Face the New Century, London: Zed Press, 2000. 29 UNFPA, State of the World’s Population 2000. 30 S Jejeebhoy, and S Bott, ‘Nonconsensual sexual experiences of young people: A review of the evidence from developing countries’, New Delhi, India: Population Council Regional Working Papers No. 16, 2003. 31 G Sodhi, and M Verma, ‘Sexual coercion amongst unmarried adolescents of an urban slum in India’, in Towards Adulthood: Exploring the Sexual and Reproductive Health of Adolescents in South Asia, S Bott, S Jejeebhoy, I Shah and C Pur, (eds), Geneva: World Health Organisation, pp. 91–94, 2003. 32 World Bank, World Development Report 1993: Investing in Health, New York: Oxford University Press, 1993. 33 A R Morrison, and M B Orlando, 1999. 34 M A Cohen, ‘Pain, suffering, and jury awards: a study of the cost of crime to victims’, Law and Society Review, 22, 537-555, 1988a. 22
  • 24. 35 T R Miller, M A Cohen, and S B Rossman, ‘Victim costs of violent crime and resulting injuries’, Health Affairs, 12, 186-197, 1993. 36 A M Moe, and M Bell, ‘Abject economics: The effects of battering and violence on women’s work and employability’, Violence Against Women, Vol. 10, No. 1, 29-55, New York: Sage Publications, 2004. 37 World Health Organisation (WHO), The Economic Dimensions of Interpersonal Violence, Geneva: WHO, 2004. 38 Development & Training Services (DTS) Consortium, Unsafe Schools: A Literature Review of School-Related Gender-Based Violence in Developing Countries, Arlington, VA: DTS, Inc., 2003. 39 Human Rights Watch 2001. 40 S Rossetti, Children in School: A Safe Place? Botswana: UNESCO, 2001. 41 S Hallam, ‘Crimes without punishment: Sexual harassment and violence against female students in schools and universities in Africa’, Discussion Paper No. 4. London: Africa Rights, 1994. 42 D Terefe, and D Mengistu, ‘Violence in Ethiopian schools: A study of some schools in Addis Ababa’, in Violence at Schools: Global Issues and Interventions, T. Ohsako (ed.). Paris: UNESCO International Bureau of Education, 1997. 43 C A Varga 1997. 44 K Wood, and R Jewkes 1997. 45 C Varga, and L. Makubalo, 1996. 46 K Wood, and R Jewkes 1997. 47 South Africa Department of Health, ‘South Africa Demographic and Health Survey 1998: Full Report’, Pretoria: South Africa Department of Health, 1999. 48 A follow-up validation study indicates significant under-reporting of both physical and sexual violence. South Africa Department of Health, South Africa Demographic and Health Survey 1998: Full Report, Pretoria: South Africa Department of Health, 1999. 49 R Jewkes et al., ‘Rape of girls in South Africa’, Lancet, 359 (9303), 319–20, 2002. 50 South Africa Department of Education, The development of education: Country report of South Africa. Pretoria, 2004. 51 In 2001, 96 percent, 72 percent, and 45 percent of 14-, 18-, and 20-year-olds, respectively, were attending school below the tertiary level 79 52 K Hallman and M Grant, “Poverty, educational attainment, and livelihoods: How well do young people fare in KwaZulu Natal, South Africa?” Horizons Research Summary, Population Council. Washington, D.C. 2004. http://www.popcouncil.org/pdfs/horizons/ythkznsum.pdf 53 D Lam, and J Seekings, ‘Transitions to adulthood in urban South Africa: Evidence from a panel survey’, Paper prepared for IUSSP General Conference 2005, Tours, France, 2005. 54 In the 1998 Demographic and Health Survey, thirty-five percent of 19 year-olds had been pregnant and thirty percent were already mothers (South Africa Department of Health 1999). 23
  • 25. 55 K Hallman and M Grant 2004 56 C Kaufman, T de Wet, and J Stadler, ‘Adolescent pregnancy and parenthood in South Africa’, Studies in Family Planning, 32(2), 147–160, 2001. 57 R Magnani et al. 2005 58 A G Turner, R J Magnani, and M Shuaib. ‘A not quite as quick alternative to the expanded programme on immunization (EPI) cluster survey design’, International Journal of Epidemiology, 25, 198-203, 1996. 59 Jejeebhoy and Bott (2003)80 estimate that 15 to 30 percent of first female sexual experiences were forced. A recent national survey of young people in South Africa (Pettifor et al. 2004)81 shows that 98 percent of young men reported they “really wanted” or “wanted” to have sex their first time, versus only 71 percent of young women. Campbell (2003)82 reports that rape and emotional pressure are common in young people’s first sexual experiences in a mining community outside of Johannesburg. Using the Transitions data, Hallman (2004)83 reports that only 55 percent of females versus 94 percent of males age 14-24 who have had sex report themselves as having been “willing” at their first sexual encounter (versus those who were persuaded, tricked, forced, or raped). 60 H Brookes and Higson-Smith 2004. 61 S Jejeebhoy, and S Bott 2003. 62 K Hallman and M Grant 2004. 63 A delay is defined as a year of non-advancement because of either not having enrolled at all during a particular year but having eventually returned to school, withdrawal during a year, or repeating a grade because of poor performance. 64 W H Greene, Econometric Analysis, 5th edition, Upper Saddle River, NJ: Prentice-Hall, 2003. 65 Among 20-24-year-olds, attainment of matriculation certificate is technically a censored outcome since 29% of this group were still attending secondary school. Evidence from South Africa suggests, however, that very few of these will go on to receive their matriculation certificate (Statistics South Africa 2005)84. Attainment of the certificate is therefore treated as a binary outcome. 66 Certification of successful secondary school completion. 67 S Jejeebhoy, and S Bott 2003. 68 V J Whitefield, ‘A descriptive study of abusive dating relationships among adolescents’, MA Thesis, University of Cape Town, South Africa, 1999. 69 K Hallman, ‘Socioeconomic disadvantage and unsafe sexual behaviors of young women and men in South Africa’, Policy Research Division Working Paper No. 190, Population Council. New York, NY, 2004. http://www.popcouncil.org/publications/wp/prd/rdwplist.html#2004 70 Health Systems Trust 2000. 71 South Africa Department of Education 2004. 72 S Jejeebhoy, and S Bott 2003. 73 Y Cheng, B Kang, T Wang, X Han et al., ‘Case-controlled study on relevant factors of adolescent sexual coercion in China,’ Contraception, 64, 77–80, 2001. 24
  • 26. 74 V Patel, and G Andrew, ‘Gender, sexual abuse and risk behaviours in adolescents: A cross-sectional survey in schools in Goa’, National Medical Journal of India, 14(5), 263–267, 2001. 75 Human Rights Watch, ‘Suffering in silence: The links between human rights abuses and HIV transmission to girls in Zambia’, New York: Human Rights Watch, 2002. 76 National Research Council and Institute of Medicine. Growing up global: The changing transitions to adulthood in developing countries. Panel on Transitions to Adulthood in Developing Countries. Cynthia B. Lloyd, ed. Committee on Population and Board on Children, Youth, and Families. Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press, 2005. 77 S Jejeebhoy, and S Bott 2003. 77 South Africa Department of Health, ‘South Africa Demographic and Health Survey 1998: Full Report’, Pretoria: South Africa Department of Health, 1999. 78 S Rasool, S, K Vermaak, R Pharaoah, A Louw, A Stavrou A, Violence Against Women: A National Survey, Pretoria: Institute for Security Studies, 2002. 79 Statistics South Africa, ‘Stages in the life cycle of South Africans,’ Pretoria: South Africa, 2005. 80 S Jejeebhoy, and S Bott 2003. 81 A E Pettifor, H V Rees, A Steffenson, L Hlongwa-Madikizela, C MacPhail, K Vermaak, and I Kleinschmidt, ‘HIV and sexual behavior among young South Africans: A national survey of 15-24 year olds,’ Johannesburg: Reproductive Health Research Unit, University of the Witwatersrand, 2004. 82 C Campbell 2003. 83 K Hallman 2004. 84 Statistics South Africa 2005. 25