Hegemonic Masculinity,Violence,and Gender Equality

Abstract

Messerschmidt and colleagues have pioneered work in criminology using masculinities theory, yet many researchers in the field have not engaged with the possibility that the different patterning of correlated violent, sexually risky, and antisocial behaviors may reflect a disaggregation of the category of men into multiple masculinities. This lens can help understand men’s violence and enable intervention targeting. We analyzed household survey data and identified three classes of men according to their use of violence and correlated behavior. Associations between masculinity categories and other acts of violence (against women), gender attitudes, and sexually transmitted diseases showed a dose–response relationship across the masculinity categories. Structural equation modeling showed how the psychological variables mediated pathways between exposure to trauma and teasing in childhood and the more violent masculinity categories. Our analysis provides a bridge between gender analysis (with intersectionality) and the psychoanalytic in understanding men’s violence. This is important for interventions to prevent men’s violence against women and other men and support arguments for targeting violence prevention interventions.

Keywords

masculinities latent class analysis gender-based violence rape transactional sex sexual risk-taking crime childhood trauma

There is a growing body of quantitative research on male ideas and behavior which shows that many men have gender inequitable attitudes and engage in forms of risky and exploitative sexual behavior, general acts of violence, and violence against women. This research increasingly suggests that these ideas and behaviors track together such that men who rape are also more likely, than those who do not, to physically abuse and control women, have transactional sex, weapons, fight with other men and be gender inequitable in their ideas, and the same applies for these other behaviors (Jewkes and Morrell 2010; Jewkes et al. 2011; Dunkle et al. 2006, 2007; Jewkes et al. 2012b; Fulu et al. 2013; Jewkes et al. 2013; Barker et al. 2011). Thus, among men, there seems to be a clustering of antisocial and violent ideas and behaviors and gender inequitable attitudes.

The observation that behaviors cluster, and thus that some men engage in more violent and antisocial behaviors of a range of types than others, has parallels which are born out in observations from criminology. These are that a small proportion (1 percent to 10 percent in various studies) of men account for over half of all convictions. For example, a Swedish study found that 1.0 percent of the total population (overwhelmingly men) accounted for 63.2 percent of all convictions (Falk et al. 2014) and the Cambridge Study in Delinquent Development found that 7 percent of their sample of 411 men accounted for over half of the convictions (Farrington et al. 2006). A notable feature of these papers, and the broader discipline, is that with the exception of a few authors (notably Messerschmidt 1993, 1997, 2000, 2012; Newburn and Stanko 1994), the gendered nature of male crime has been ignored or is a topic of active disagreement (Collier 1998; Hood-Williams 2001; Mullins 2010). There has usually been no attempt at theoretical linkage, even within feminist criminology, apart from observations that violent and antisocial behavior is much more common among males, between these types of contributions in the criminological literature to the literature of critical men’s studies (Mullins 2010). Yet the analysis of clustering of violent and sexually risky behaviors and their roots in gender inequity described above suggests that there may be important connections and this was very comprehensively argued by Messerschmidt (1993) in his classic text.

A reading of the clustering of violent and antisocial behavior is that it empirically supports ideas of multiple masculinities and the existence of differences among men expressed through positions on gender, use of violence toward and control of women, sexual risk-taking, and use of violence and expressions of toughness among men. Connell’s analysis of masculinities, within the broader framework of gender and power, is an important theoretical reference point in this regard (Connell 1987; Messerschmidt 1993). Connell argues that masculinities are multiple in a given society, but one position, a particular configuration of male attitudes and practices, is hegemonic and serves to perpetuate gender inequality (men’s domination over women) and assumes power over other (often minority groups of) men. The concept of hegemonic masculinity has been widely used, as well as debated and refined (R. W. Connell and Messerschmidt 2005), but the basic idea is that hegemonic masculinity is a culturally idealized form of masculinity and “is both a personal and a collective project” (Donaldson 1993, p. 645). A core element of the construction of hegemonic masculinity is heterosexuality, and to a greater or lesser extent, hegemonic masculinity is constructed as a gender position which is as much “not gay” as it is “not female.” With these characteristics, one can assume that essential features of the current configuration of hegemonic masculinity include performance of heterosexuality, dominance and control over women, and competition among men. Although masculinity is fluid, and there has been a notable shift in northern masculinities and among the middle class in the South (Anderson 2009), in many parts of the world, these constitutive elements are still in place and have been empirically described, even if there is evidence of gender change (Wood and Jewkes 2001).

Connell also argued that masculinities are fluid and dynamic and may also be seen as positions that are occupied situationally, in that the position occupied, practices, and values espoused in one context may be different from those of another. Therein this poses a problem for quantitative research into masculine positions, as the use of survey assessment and analysis “fixes” positions, in a snapshot, which could be seen as anathema for a concept which is theorized as dynamic. A further problem is that there are debates about hegemonic masculinity that have become locked in an impasse of seeing the concept either as aspirational or as descriptive of general, society-wide power (R. W. Connell and Messerschmidt 2005; Beasley 2008; Howson 2014). If hegemony is not expressed in action flowing from ideal but only describes society-wide power, it would be very hard to investigate quantitatively. This has been viewed as an obstacle to quantitative sociological research on masculinities and men’s violence and antisocial behavior (Mullins 2010). It in turn limits the analytical utility of hegemonic masculinity because it suggests that it can only be described and never measured, that it is mercurial, and that it is hard to grasp. This has implications for many gender organizations who work for gender equality and who assume that a particular form of masculinity is hegemonic and then seek to reform or transform this construction or configuration. If their assumption is wrong, their interventions might be wrongly targeted (cf. Jewkes et al. 2015).

However, there are quantitative analytical methods that can be applied to a data set that enables an empirical analysis of male ideals and practices. One example is the derivation of latent variables and classes, which requires coherence of measured practices and/or attitudes in order to be successful. This has not been previously applied to these research questions and thus it has not been previously shown that it is possible to identify particular clusters of men’s actions and attitudes and to create a framework that distinguishes groups of men in relation to gender equality. The successful use of these methods to identify and describe groups of men who are either more or less violent in itself enables us to move beyond the previously mentioned impasse, but also may have major implications for gender interventions, potentially targeting and tracking impact. It can also enable us to see how multiple masculinities operate and have effect in the social world and investigate how actions and aspirations interact and trace their developmental origins.

The aim of this article is first to use statistical methods to identify different masculine positions based on the probability of engagement in different male practices in a large data set from a household survey conducted with adult men in two provinces of South Africa. Second, to describe the statistical correlates of these positions both through examining childhood and psychological factors associated with each and through the use of structural equation modeling. The third aim is to describe the correlations of these gender (masculinity) positions with other male attitudes and practices and through this to discuss how these masculinity positions affect current understandings of public health challenges and interventions.

Method

A cross-sectional study was conducted in 2008 in three adjoining districts of the Eastern Cape and KwaZulu-Natal provinces of South Africa, spanning rural areas, commercial farmland, towns, and a major city. Detailed methods are described elsewhere (Jewkes et al. 2009). A population-based sample of men aged eighteen to forty-nine years was identified using a multistage proportionate sampling design. Census enumeration areas (EAs) were the primary sampling units, and the sample was drawn from those in the 2001 census by Statistics South Africa, stratified by district and proportionate to population size. Within each EA, we mapped all households, randomly sampled twenty households, enumerated the eligible men who slept there within the previous night, and randomly selected one. There was no replacement of households without an eligible man.

Among 222 sampled EAs, 2 (0.9 percent) had no human dwellings. In the remaining 220, 1 (0.45 percent) was excluded because gatekeepers refused access, and 4 (1.8 percent) were excluded because no homes with eligible men were identified following multiple visits at different times of day. We sampled a total of 4,473 visiting points. Of these, 822 (18.4 percent) could not be rostered for eligibility after a minimum of three attempts at contact. Among the remaining 3,651 visiting points, 1,353 (37.1 percent) were found to contain no eligible man, while 2,298 (62.9 percent) contained at least one eligible man. We thus estimated a total eligible population of 2,815 men in our sampling frame. Of this estimated population, 27 percent could not be contacted (estimated n = 760), 10.5 percent (n = 296) refused to participate, 0.7 percent (n = 21) agreed to complete interviews but then either withdrew or failed to provide any usable data, and 61.7 percent (n = 1,737) completed the questionnaire. Interviews were thus completed in 215 (97.7 percent) of the 220 eligible EAs and in 1,737 (75.6 percent) of the 2,298 enumerated and eligible households. Of these, 1,220 (70.2 percent) also provided dried blood spots (DBS) for HIV testing. These participation rates compare favorably to those obtained in other population-based surveys in South Africa.

Participants self-completed a survey using audio-enhanced personal digital assistants (PDA). The text of each question and associated answer choices were presented on the PDA screen, while an accompanying voice recording read the question and answers aloud. Participants listened through headphones and answered by tapping their answer choice with a stylus. The questions could be read, or listened to, in isiXhosa or isiZulu and English. This environment provided complete privacy for respondents. Fieldworkers were nearby during questionnaire completion so they could assist respondents if requested, but interviews were otherwise private. Questions included demographics, socioeconomic status (SES), childhood variables, relationship and sexual histories, psychological measures, and detailed questions on perpetration of violence.

Measures

The questionnaire included categorical variables measuring age and income. Questions on men’s childhoods included items on whether and how often their father was at home. Scales measured men’s perceptions of the kindness of their mother (three items, Cronbach’s α = .75) and father (four items, Cronbach’s α = .87). A typical item was “I had a loving relationship with my mother/father while I was growing up.” A four-point Likert-type response scale was used. Men were asked if they had been teased or harassed as a child.

Data on adverse experiences before the age of eighteen were collected using a locally modified version of the short form of the Childhood Trauma Questionnaire (Jewkes et al. 2010; Bernstein et al. 2003). We assessed five dimensions of adversity: emotional neglect, emotional abuse, physical neglect/hardship, physical abuse, and sexual abuse using a four-point response scale (never, sometimes, often, and very often; Cronbach’s α = .79). A typical question was “before I reached eighteen one or both of my parents were too drunk to take care of me.” Men were asked if they had ever been raped by a man (persuaded or forced to have sex when you did not want to).

Data were collected on two dimensions of psychopathy. Blame externalization and Machiavellian egocentricity are two core affective and interpersonal deficits of psychopathy (Lilienfield 2005). Blame externalization is a perception of the world as hostile and others being at fault for one’s problems and Machiavellian egocentricity is a measure of narcissism and ruthless attitudes toward others (Lilienfield 2005). Thirteen questions on Machiavellian Egocentricity and Blame Externalization subscales of the Psychopathic Personality Inventory–Revised (PPI-I) were included. The Cronbach’s α for the scales together were .83. A typical item on the Machiavellian Egocentricity subscale was “I get mad if I don’t receive special favors I deserve” and on the Blame Externalization subscale was “I have often been betrayed by people I trust.” Each has a four-level response option (false, mostly false, mostly true, and true). We dichotomized the scales and present the proportion scoring in the upper third of the scale versus the lower two-thirds. For blame externalization, 28.4 percent were in the upper third and for Machiavellian egocentricity, 18.5 percent were in the upper third. These were adapted and reproduced by special permission of the Publisher Psychological Assessment Resources, Inc., 16204 North Florida Avenue, Lutz, FL 33549, from the PPI-I by Scott O. Lilienfield, PhD, Copyright 2005 by PAR, Inc. Further reproduction is prohibited without the permission of PAR, Inc.

We asked four items to measure empathy, adapted from Abbey et al (2006; Cronbach’s α = .80). A typical item was “I am often touched by things that I see happen.” These had a five-point response scale (doesn’t describe me well—describes me well). Perceptions of life success were assessed with the following question: “If you compare your life circumstances overall now with those of the people you grew up with, would you say you have done much better for yourself, somewhat better, the same, less well, much less well?”

Attitudes toward gender relations were measured using ten items from the Gender Equitable Men (GEM) scale (Pulerwitz and Barker 2008; Cronbach’s α = .78). A typical item is “There are times when a woman deserves to be beaten.” A high score denotes more equitable attitudes. The school bullying perpetration score was an eight-item scale used to measure experiences with sexual bullying at school with four-level response options (never, sometimes, often, and very often; Cronbach’s α = .76). These questions were developed for the study. A typical item was “My school friends and I were a group and we would put pressure on a girl to date one of us until she agreed.”

We asked eleven items about lifetime experiences of participation in crime. These were modified for the local context from Tremblay et al. (1995) who developed them as a measure of delinquency in childhood. Eight of the items related to theft (Cronbach’s α = .81) and a typical item was “how often have you stolen an animal from someone?” The response options were never, once, two to three times, and more often. Men were also asked about weapons ownership, possession, and arrests.

Recent alcohol consumption in the past twelve months was assessed through a question on frequency of having five or more drinks per drinking day. Drug use was assessed through a question on how often the man had smoked dagga (cannabis) in the past twelve months. This drug was selected, as it grows well locally and is cheap and so is most widely used, and most men who use other drugs use this too. Men were asked if they had ever been in a gang.

Practices of gender relations were measured through questions about number of sexual partners, whether men had had makhwapheni in the past year or ever (a usually secret concurrent partner), and about transactional sex with women, defined as sex that was primarily motivated by a desire for material gain on the part of the woman. This was defined as providing food, cosmetics, clothes, transportation, items for children or family, school fees, somewhere to sleep, handyman work, or cash (Jewkes et al. 2012c). Men were asked about lifetime perpetration of physical intimate partner violence (IPV), using the modified World Health Organization violence against women instrument (Garcia-Moreno et al. 2005). Specific acts of violence were asked in five items ranging from slapping to threats with or use of a weapon. A twelve-item scale assessed men’s control in their relationship, after Pulerwitz, Gortmaker, and DeJong (2000), as adapted for South Africa by Dunkle et al. (2004). These items were summed to derive a score (Cronbach’s α = .78). A typical question was “when I want sex I expect her to agree.”

Rape perpetration was assessed using seven questions developed for the study and validated through cognitive interviewing, none of which actually used the word “rape” (Sikweyiya, Jewkes, and Morrell 2007). They were modifications of those used previously in the Eastern Cape (Jewkes et al. 2006). A typical item was “How many times have you slept with a woman or girl when she didn’t consent to sex or after you forced her?” The questions additionally asked about having forced a (former) girlfriend or wife into sex, having forced a woman who was not a girlfriend or wife into sex, and having sex with a woman who was too drunk to consent. Two questions assessed multiple perpetrator rape perpetration. Men were also asked if they had ever raped a man.

HIV

Participants were also asked for a finger-prick blood spot that was dried for HIV testing. DBS were tested for HIV with a screening ELISA (Genscreen Bio-Rad, Steenvorde, France) and positive results were confirmed with a second ELISA (Vironostika, bioMérieux, Marcy d’Etoile, France). Men who declined to give blood for HIV did not differ significantly from those who did in age, race, circumcision, history of consensual men having sex with men (MSM) activity, or perpetration of sexual violence. However, men who had completed secondary education were significantly less likely to provide blood (66.6 percent vs. 75.1 percent, p = .0003).

Ethics

Ethics approval was granted by the Medical Research Council’s Ethics Committee. Participants signed informed consent separately for interviews and DBS. An incentive of ZAR 25 (∼US$3.5) was offered for each component, giving a total of ZAR 50 for both. The PDAs ensured that participant answers were entirely anonymous, and we retained no identifying information on any participant. This was necessary to protect participants reporting illegal activities from possible repercussions. It also meant that HIV results could not be given. Free HIV testing is widely available from government clinics in South Africa and all participants were advised to learn their status.

Data Analysis

The sample was self-weighting. Questionnaire data were linked to HIV data using anonymous codes. Most of the analyses were performed using Stata 12.0 and accounted for the two-stage sampling structure, with stratification by district and data clustered in EAs. No imputation methods were used to replace missing data.

The latent class analysis was conducted in MPlus, ver. 7 with R used to more easily present the results. The initial variables used for class determination were those which had been hypothesized from previous research to measure male behaviors and attitudes which were indicative of potential types of masculinities. We tested four- and three-class models. We tested a range of variables which included those shown in Table 1 as well as gang membership, problem drinking, not paying maintenance for a child, gender attitudes, controlling behaviors, having raped, and bullying. We also tested a range of positive male behaviors, but these did not load coherently into classes. The best fitting classes were three in number and the following model fit were the statistics: AIC = 12,466.77 and BIC = 12,592.35, percentage of two-way marginal residuals > 4:1 and sum of two-way marginal residuals large, out of twenty-one pairs:1. We have numbered the most violent #1 and most moderate category #3.

Table 1.

Measurement Probabilities of Variables Loading on the Masculinity Classes.

Variable	Measurement Probabilities
Variable	High (24.7% of Men)	Medium (29.6% of Men)	Lower Violence (45.7% of Men)
Has illegal gun	0.476	0	0
Has a weapon	1	.091	.093
>1 Episode of physical or sexual IPV	0.573	.406	.099
Has a khwapheni	0.8	.845	.268
Has had sex with a sex worker	0.4	.24	.015
Has had transactional sex	0.851	.86	.354
Drug use in the past year	0.631	.462	.157

Note: IPV= intimate partner violence.

The distributions of sociodemographic characteristics and childhood variables by masculinity category were summarized as percentages (or means) using standard methods for estimating confidence intervals from complex multistage sample surveys (Taylor linearization). Pearson’s χ² was used to test two-way associations between categorical variables. A multinomial regression was used to model the social and demographic characteristics associated with each masculinity category. A second multinomial regression model was built to show associations between childhood characteristics and the masculinity categories, adjusted for age, race, and income. A third such model included psychological variables, adjusted for childhood and social and demographic variables. For each of the variables in Table 5, a separate multinomial regression model was built with the relationship variable, violent practice, or sexual health problem as the dependent variable and the masculinity categories, age, race, and income as independent variables.

The structural equation model (SEM) was built in Stata 13.0 to examine pathways to the masculinity categories. The variables included were those used for the psychological variables multinomial regression model and the other nonsignificant childhood variables, with the exception that income was replaced by a measure of SES which had greater variability and thus measurement properties for the model. These variables included all those in the data set that may have been considered as causal. The SES measure used three asset ownership variables, home wall building materials, frequency of hunger, and not eating meat due to lack of money, and ease of emergency resource mobilization (Cronbach’s α = .643). Initially, a measurement model was fitted and then a maximum likelihood estimation with missing values. Nonsignificant pathways were deleted and modification indices reviewed and adjusted to optimize model fit. The model presented is adjusted for race. The model fit for the final was good as shown by the fit statistics (p = .094, RMSEA = .018, CFI = .995, and TLI = .986).

Results

The best fit was found for a three-class model encompassing the set of seven violent or sexually risky male behaviors as shown in Table 1. These included two weapons possession measures, illegal gun possession and having a weapon; one intimate partner violence measure, having a khwapheni (concurrent additional sexual partner); two measures of providing material resources for sex, having had sex with a sex worker and having had transactional sex and having used illegal drugs in the past year. The model fit statistics showed that this fitted the data well.

The table shows that the greatest difference between the high and other two categories was in weapons ownership. The middle category resembled the high one in that most men (over 80 percent) had had transactional sex and had a khwapheni. For having had sex with a sex worker, past year drug use, and intimate partner violence, the middle category probability was roughly midway between that of the high and the low categories. Some of the men in the low violence category had previously used violence or were ready to do so. One in ten had a weapon and had perpetrated more than one episode of physical or sexual violence against a woman partner. However, they were much more law abiding, in that none had an illegal gun and fewer than 2 percent had ever had sex with a sex worker, and only 16 percent had used drugs (mainly cannabis) in the past year.

The procedures above resulted in the men falling into three categories: 24.7 percent were in the highly violent/antisocial category, 29.6 percent in the medium violence category, and 45.7 percent in the lowest violence/most pro-social category. Examination of the social and demographic characteristics of the men shows that the categorization of men was associated with their age, race, income, education, and marital status. In the sample overall, half the men interviewed were under twenty-five years of age (see Table 2). Men in the high- and mid-violence categories were younger than those in the low-violence category. There were racial differences, with those in the high-violence category significantly more likely to be colored than those in the low-violence category. There were also differences in income, and those in the high-violence category had significantly higher income than those in the low-violence category, with differences in income between the middle- and low-violence categories only being visible for the low paid group (vs. unpaid). Men in the low-violence category were less well educated than those in the higher category and less likely to be cohabitating.

Table 2.

Social and Demographic Factors Associated with the Masculinity Categories.

Variable	High (24.7% of Men; %)	Medium (29.6% of Men; %)	Lower Violence (45.7% of Men; %)	p Value	Multinomial Model of Social and Demographic Factors Associated with Masculinity Category
					High versus Low				Medium versus Low
					RRR	95%CI		p Value	RRR	95%CI		p Value
Age: eighteen to twenty-four years	54.7	48.8	51.6	.0002	1.00				1.00
Twenty-five to thirty-four years	32.7	35.6	26.7		0.95	0.69	1.30	.73	1.35	1.01	1.81	.04
Thirty-five years and over	12.6	15.6	21.7		0.48	0.31	0.73	.001	0.80	0.57	1.13	.21
Race: African	77.8	88.3	86.8	<.0001	1.00				1.00
Colored	8.2	4.1	1.9		3.82	1.75	8.35	.001	1.87	0.93	3.75	.08
Indian	12.2	6.4	9.6		1.37	0.81	2.32	.23	0.75	0.45	1.24	.26
White	1.9	1.2	1.8		1.66	0.66	4.15	.28	0.98	0.32	3.03	.97
Income: None	39.0	47.6	55.4	<.0001	1.00				1.00
Up to ZAR 2000/month	45.2	40.9	32.8		2.02	1.48	2.76	<.0001	1.46	1.11	1.93	.007
Over	15.9	11.5	11.6		1.91	1.20	3.04	.007	1.13	0.72	1.78	.60
Education: Matric plus	43.0	41.6	38.6	.024	1.08	0.83	1.39	.56	1.15	0.89	1.48	.30
Marital status: Married	18.7	19.7	26.2	.0008	1.00				1.00
Cohabiting	13.4	14.3	8.5		2.22	1.45	3.39	<.0001	2.19	1.41	3.39	.001
Divorced/ widowed	4.5	3.0	3.5		1.88	0.98	3.63	.06	1.28	0.63	2.57	.50
Single	63.5	63.1	61.9		1.35	0.98	1.85	.07	1.30	0.97	1.76	.08

Note: CI = confidence interval; RRR = relative risk ratio.

Table 3 presents data on some of the childhood circumstances and trauma exposures of men in the different categories. Overall, the categorization of men was associated with their experience of being teased as children, how kind their father was and their exposure to trauma in childhood overall based on a score which encompassed physical, sexual and emotional abuse, and physical and emotional neglect. Men in the high- and medium-violence levels were both significantly more likely to have been teased and also to have experienced childhood trauma than those in the low-violence group. Men in the high-violence group were significantly less likely to rate their father as kind than those in the low-violence group.

Table 3.

Relationship practices, violent behaviour and outcomes and sexual health associated with the masculinity categories.

Variable	High	Medium	Lower Violence	p Value	Multinomial’ Model of Childhood Factors Associated with Masculinity Category, Adjusted for Age, Race, and Income
					High versus Low				Medium versus Low
					RRR	95%CI		p Value	RRR	95%CI		p Value
Childhood characteristics
Mother rarely or never at home	41.43	42.35	38.89	.46	0.98	0.71	1.33	.88	1.17	0.89	1.54	.25
Father rarely or never at home	69.21	68.38	65.91	.47	0.95	0.68	1.34	.78	1.02	0.78	1.35	.87
Teased by others	66.82	57.53	45.84	<.0001	2.31	1.72	3.10	<.0001	1.53	1.17	1.99	.002
Father kindness score (mean)	11.11	12.12	12.2	<.0001	0.95	0.91	0.99	.02	1.02	0.98	1.07	.28
Mother kindness score (mean)	10.73	10.81	10.82	.401	1.03	0.94	1.13	.50	1.02	0.94	1.10	.68
Childhood trauma score	20.65	19.39	18.36	<.0001	1.07	1.04	1.10	<.0001	1.03	1.00	1.06	.03
Psychological characteristics					Multinomial’ model of associations between psychological characteristics and masculinity categories, adjusted for age, race, income, and childhood characteristics
Machiavellian egocentricity: Cut	27.6	21.6	10.8	<.0001	2.47	1.72	3.52	<0.0001	2.03	1.42	2.91	<0.0001
Blame externalization: Cut	54.7	38.3	24.0	<.0001	3.17	2.28	4.05	<0.0001	1.89	1.41	2.53	<0.0001
Empathy	48.2	49.5	57.6	.004	0.97	0.94	1.00	0.046	0.97	0.95	1.00	0.031

Note: CI = confidence interval.

The table also shows that exhibiting high levels of Machiavellian egocentricity, blame externalization, and empathy were all associated with the masculinity categories, after adjustment for social and demographic characteristics and childhood trauma exposures. In the case of Machiavellian egocentricity and blame externalization, a dose–response relationship is visible across the categories.

A structural equation model (SEM) of antecedents of the masculinity categories is presented in Figure 1 and Table 4. The model shows a path linking SES and masculinity categories mediated by empathy, such that men of higher SES are more empathetic and demonstrate less violent and more pro-social behavior. Paths between SES and masculinity categories were also mediated by childhood trauma and teasing, such that men of lower SES would experience more teasing and childhood trauma. Both of these directly enhanced the likelihood of being in a more violent masculinity category. However, the path between childhood trauma and the masculinity categories was further mediated by Machiavellian egocentricity and blame externalization, such that men experiencing more childhood trauma were more likely to have higher scores on these and hence a more violent masculinity categorization. A path between experience of teasing and more violent masculinity categorization was also mediated through blame externalization. The model also shows that having a kind father can provide protection against teasing, and this also directly impacts (reduces) the risk of becoming a more violent man.

Figure 1.

Structural equation model of antecedents of the masculinity categories (higher categories are less violent).

Table 4.

Path Model: Direct Effects, Disturbance Variances, and Equation-level Goodness of Fit.

Parameter	Standardized Coefficients	SE	z	p > \|z\|	[95% Confidence Interval]
Direct effects
SES → empathy	0.466	0.046	10.48	<.0001	0.379	0.554
SES → childhood trauma	−0.227	0.042	−5.44	<.0001	−0.309	−0.145
SES → teased	−0.008	0.004	−2.09	.036	−0.016	−0.001
Kind father → teased	−0.017	0.004	−4.91	<.0001	−0.024	−0.010
SES → race	0.054	0.005	10.93	<.0001	0.045	0.064
Childhood trauma → Machiavellian egocentricity	0.226	0.028	8.06	<.0001	0.171	0.280
Race → Machiavellian egocentricity	−0.907	0.220	−4.13	<.0001	−1.34	−0.477
Empathy → masculinities categories	0.007	0.004	2.03	.043	0.000	0.014
Childhood trauma → masculinities categories	−0.010	0.004	−2.50	.012	−0.018	−0.002
Teased → masculinities categories	−0.119	0.039	−3.03	.002	−0.195	−0.042
Machiavellian egocentricity → masculinities categories	−0.017	0.004	−4.30	<.0001	−0.024	−0.009
Blame externalization → masculinities categories	−0.031	0.004	−8.35	<.0001	−0.039	−0.024
Kind father → masculinities categories	0.015	0.006	0.264	.008	0.004	0.026
Race → masculinities categories	−0.093	0.029	−3.180	.001	−0.150	−0.036
Race → Kind father	0.556	0.132	4.210	.000	0.297	0.815
Childhood trauma → Blame externalization	0.191	0.030	6.47	<.0001	0.133	0.249
Race → Blame externalization	0.886	0.221	4.000	.000	0.452	1.319
Teased → Blame externalization	2.51	0.294	8.53	<.0001	1.93	3.09
Disturbance variances	Estimate	SE			[95% confidence interval]
Empathy	29.17	1.06			27.16	31.32
Childhood trauma	25.19	0.882			23.52	26.98
Teased	0.244	0.008			0.228	0.261
Machiavellian egocentricity	30.39	1.09			28.32	32.6
Masculinities categories	0.567	0.019			0.531	0.607
Blame externalization	31.18	1.11			29.07	33.44
Kind father	11.87	0.415			11.09	12.72
Race	0.380	0.0130322			0.3549992	0.406
SES	10.04	0.366			9.35	10.79
Equation-level goodness of fit	R ²
Empathy	.0697
Childhood trauma	.0249
Teased	.0177
Machiavellian egocentricity	.0547
Masculinities categories	.1383
Blame externalization	.0980
Kind father	.0105
Race	.0727

Note: mc² is the Bentler–Raykov squared multiple correlation coefficient. SE = standard error; SES = socioeconomic status.

The more violent masculinity categories were seen in the multinomial models to be significantly associated with both self-reporting more controlling practices in men’s relationships and expressing less equitable gender attitudes (Table 5). They were also associated with a range of violent behaviors (rape of a man or woman, theft or robbery, and bullying others), experience of being raped by a man, and the outcome of having ever been in prison. In all of these, there was a dose–response relationship. Men in the more violent masculinity categories were more likely to have ever had a genital ulcer and penile discharge. They were not more likely to have HIV or always use a condom.

Table 5.

Social and Demographic Factors Associated with the Masculinity Categories.

Variable	Column Percentages Showing % of Men with the Variable in Each Category				RRR/coefficient Calculated in multinomial Models with the Relationship Practice, Violent Behavior, or Sexual Health Problem as the Independent Variable and Masculinity Categories as an Exposure, Adjusted for Age, Race, and Income
	High	Medium	Lower violence	p Value	High versus Low				Medium versus Low
	High	Medium	Lower violence	p Value	RRR/coeff	95%CI		p Value	RRR/coeff	95%CI		p Value
Relationship practices
Relationship control scale (mean)	13.4	13.8	12.8	<.0001	0.60	0.22	0.98	.002	0.95	0.60	1.31	<.0001
GEM scale (mean)	11.6	11.4	12.0	.016	−0.39	−0.74	−0.03	.034	−0.50	−0.83	−0.17	.003
Violent behavior and outcomes
Any rape	51.9	29.8	12.1	<.0001	8.44	6.14	11.62	<.0001	3.03	2.22	4.14	<.0001
Theft or robbery three plus times	65.1	29.1	17.5	<.0001	10.35	7.44	14.40	<.0001	2.05	1.49	2.81	<.0001
Rape of a man	6.6	2.3	1.2	<.0001	6.39	2.32	17.59	<.0001	2.73	0.94	7.94	.065
Raped by a man	14.1	12.1	5.3	<.0001	3.19	2.02	5.04	<.0001	2.45	1.57	3.81	<.0001
Bullied others many times	63.4	39.8	22.7	<.0001	6.04	4.57	7.97	<.0001	2.29	1.76	2.97	<.0001
Ever been in prison	15.0	6.3	3.9	<.0001	6.41	3.74	11.01	<.0001	2.20	1.23	3.94	.008
Sexual health problems
Ever genital ulcer	35.0	33.5	22.6	<.0001	2.42	1.81	3.25	<.0001	1.75	1.33	2.31	<.0001
HIV seropositive	17.4	20.1	17.5	.53	1.31	0.84	2.05	.24	1.12	0.74	1.69	.59
Never had a penile discharge	57.4	67.5	76.9	<.0001	0.36	0.27	0.48	<.0001	0.63	0.47	0.82	.001
Always uses a condom	35.0	38.5	39.3	.31	0.78	0.58	1.05	.10	0.97	0.74	1.28	.85

Note: CI = confidence interval; GEM = gender equitable men.

Discussion

In this household survey, it was possible to use latent class analysis to identify three coherent categories of men through testing a candidate set of male behaviors and attitudes. This technique is not often used in gender analysis. The set of variables which provided the best fit very closely matches those which have been observed to track together in previous South African research (Jewkes and Morrell 2010; Dunkle et al. 2006, 2007; Jewkes et al. 2006). The analysis supports previous observations and the derivation of a latent gender inequitable masculinity variable using structural equation modeling (SEM) in a different data set from South Africa (Jewkes et al. 2016), which have shown that violence, sexually risky, and antisocial behaviors often track together. We have shown here that although most South African men commit violent acts (and fall in the mid- or high-violence categories), nearly half of all men lean toward more respectful and less violent behavior toward women and are more law-abiding. However, among the 55 percent of men who are sometimes violent, more than half of this group are very violent, criminal, and sexually prolific. Objections to the tautological nature of the concept of masculinity and its relationship to gender-specific or patterned behaviors such as violence (Collier 1998; Hood-Williams 2001) have called into question the value of gender analysis. In this article, we seek to renew the claim for the importance of the collective gendered analysis of male behaviors and attitudes by showing how it can shed light on such behaviors and prevent a descent either into aggregated and undifferentiated or highly individualized analyses of violent behavior.

We have explored the antecedents of this categorization. Our findings strongly support a developmental psychological argument that men’s adult practice is very importantly influenced by their childhoods (Fonagy and Target 2003; Contreras et al. 2011; Walker et al. 2011; Stouthamer-Loeber et al. 2001). We have also shown the influence of structural factors (poverty), which strongly supports the well-developed arguments about the importance of intersectionality of gender and resource access (mostly called class in the literature) (Messerschmidt 1993; Bourgois 1996). While we have only a measure of current SES, given that half of the men where under twenty-five, it is unlikely that current and childhood SES for most men would have been very different. We have shown how their positioning in the more violent categories have been influenced by their experience of childhood trauma, being teased, and paternal kindness (which was protective). The SEM has confirmed theoretical perspectives on the processes through which this is likely to have occurred (e.g., Fonagy and Target 2003; Mathews, Jewkes, and Abrahams 2011; Frosh, Phoenix, and Pattman 2002). It has shown that exposure to trauma impacts on personality development as seen here in scores on measures of Machiavellian egocentricity and blame externalization, both of which are dimensions of Lilienfeld’s psychopathy scale (Lilienfield 2005), and thence on positioning in more violent masculinity categories. We have also shown how being positioned in a more violent and antisocial category predicts being more gender inequitable, more controlling with their relationship with their main partner, and prior engagement in a range of violent behaviors including rape, repeated theft or robbery, bullying, and having been in prison. It also predicts having had a sexually transmitted infection. This analysis is important, as it provides an analysis bridge between the psychoanalytic and gender analyses of men’s involvement in crime and violence and thus has the potential for advancing understanding of men and violence more broadly.

The male positions described through the latent class analysis process are not based on a random selection of male behaviors and nor are they based solely on male violent-related behaviors. Research on transactional sex and the male provider role, particularly from South Africa, has shown a strong correlation between these practices and male use of violence and engagement in crime (Dunkle et al. 2007; Jewkes et al. 2012a, 2012b). Similarly, analysis of rape perpetration in South Africa and in the United Nations multicountry study on men and violence in Asia and the Pacific has shown that this practice is strongly associated with transactional sex, as well as a range of other male violent practices against women and with other men, including gang membership and having weapons (Jewkes et al. 2011, 2013). Connell’s (1987) concept of hegemonic masculinity serves as an analytical instrument to identify those attitudes and practices among men who perpetuate gender inequality, involving both men’s domination over women and the power of some men over other (often minority groups of) men.

Masculinities are multiple, fluid, and dynamic, and hegemonic positions are not the only ones available in a given society. Our presentation of three classes of masculinity, or masculinity positions, provides an illustration of this. Although this model best fitted out data, the data set was not large enough, nor analysis sophisticated enough to exclude gradations within these classes, nor other masculinities which may be less common within the general population. We would also not like the analysis to be interpreted as indicating that masculinities are fixed, although for these men, drawing on data provided in interviews at a life snapshot point in 2008, we have fixed them in categories based on their reported practices. Several of the variables used in so doing may change over time and so individual men might move between masculinity categories.

Previous authors have identified forms of destructive and exaggerated masculinities (or hypermasculinity) (Herek 1987; Torbenfeldt Bengtsson 2015), among socially marginalized men which emphasize power and force (Totten 2003; Bourgois 1996). These are akin to the most violent category of masculinity and might be understood as a form of protest masculinity that rejects societal proscriptions against conformity to laws and the use of violence. We have shown in the SEM that indeed these are a product of poverty, combined with harshness of childhood experiences which themselves are much more commonly experienced by boys growing up in poverty. Other authors have argued that they are not entirely separate from hegemonic masculinity to the extent that they emerge out of the relationship between hegemonic ideals and (some) men’s ability to meet them. Their origins lie in adversity, including in violence experiences in childhood which have enduring psychological impact manifesting in a lack of empathy and remorse which enable acts of violence while positioning the male actors as themselves victims (Mathews, Jewkes, and Abrahams 2011; Fulu et al. 2013; Jewkes et al. 2011, 2013; Bourgois 1996). This is strongly supported by our data.

An obvious question is whether any of the masculinity positions we have described would be considered as “hegemonic”—and whether we can use any of the quantitative attributes to identify it. The lowest violence category was the numerically most dominant single category, but we caution against assuming that this would then reflect South African hegemonic masculinity. The uneven relationship between hegemony and numerical dominance has been well worn in the literature (Beasley 2008; R. W. Connell and Messerschmidt 2005; Donaldson 1993). Furthermore, many authors regard hypermasculinity as an intensification of hegemonic masculinity rather than as completely distinct. Our analysis suggests that the most violent group can be distinguished from the middle group, but there are many behavioral overlaps. Further, this analysis would lead us to conclude in itself that the category which is somewhat less violent (the middle one) would thus by definition reflect hegemonic masculinity. We are strongly drawn to this analysis in South Africa, there is a considerable body of research on hegemonic masculinity which elaborates on the situated “contents” of hegemonic masculinity and argues that demonstrating strength, toughness, and the capacity to use and often actual use of violence are very much part of hegemonic masculinity in South Africa (Morrell et al. 2013; Wood and Jewkes 2001).

The analysis presented here very clearly demonstrates the challenge of work with men to build less violent, more pro-social, and gender equitable masculinities, which is vital to promoting women and men’s health (Jewkes and Morrell 2010; Barker, Ricardo, and Nascimento 2007). Crudely put, the challenge is to shift men from being positioned in the high or middle categories toward the lower. Our analysis has shown that structural interventions to reduce poverty within families and exposure to trauma in childhood are essentially part of this process. None of the men interviewed were young enough to have benefited from South Africa’s child support grant which is payable as a cash transfer for every child in a low-income household. This has made a contribution to reducing dire poverty in families (Makiwane and Udjo 2006; Lund 2008). Understanding that gender-based and other criminal violence has a life-course development trajectory is critical for public sector policy that seeks to build a safer and more law-abiding society. We recognize that this is not a novel observation, but our findings are important to the extent that they have demonstrated through statistical analysis the roots of adult male violent and antisocial practices in men’s gender identities and linkages to all forms of violence against women and girls. Our analysis has also provided a link between these and sexually risk-taking behaviors, and related sexually transmitted infection acquisition, and provides a powerful further illustration that one part of the efforts to promote safer sexual practices should involve changing masculinities (Jewkes and Morrell 2010).

This study has limitations. The process of determining masculinity categories was limited by the variables in the data set and the number of classes was limited by its size. We would not suggest that these categories are the only one possible to find among South African men or even in the data set, but merely that they provided a good fit for the data given these constraints. Similarly with the SEM, there may have been other variables which mediate the positioning of men within masculinity categories, including measures related to social norms, but we did not have them in the data set and so are constrained by the individual-level measures available. Psychoanalytic literature on personality disorders suggests that psychopathy is likely to develop from early childhood experiences and may be genetically influenced (Johansson et al. 2008; Caspi et al. 2002). Again we did not have genetic information for the model. The study was cross sectional and so it is impossible to be sure of the temporal sequence of many of the experiences and behaviors measured. Although men’s engagement in crime, violence, and sexually risky behavior often starts in the teenage years, the childhood factors overall are likely to have preceded these and preceded the development of personality attributes. The main strength of this study is that it involved a large randomly selected sample of adult men from the general population and the survey had a good response rate. The findings should be generalizable.

Conclusion

This article shows that it is possible to use quantitative sociological techniques to identify particular clusters of men’s actions and attitudes and to create a framework that distinguishes groups of men in relation to gender equality. This enables disaggregation of the gendered category of “men” on the basis of expressed views and reported actions. This is critically important if we are to move away from essentialist research where traits are attributed on grounds of biological belonging and to begin to use quantitative methods. We have identified and described groups of men who are either more or less violent which has major implications for gender interventions. It also gives empirical support to the idea of multiple masculinities and shows how these operate and have effect in the social world and makes a contribution to debates about hegemonic masculinity that seek to move beyond the impasse of seeing the concept either as aspirational or as descriptive of general, society-wide power. We have shown that hegemony is expressed both in action and in ideal, and in South Africa, it is a threat to gender equality, and in so doing, we respond to the justifiable objection that “what hegemonic masculinity actually is” is never illuminated (Whitehead 2002). The approach that we have used shows how actions and aspirations interact and how these are causally related to SES and early childhood trauma. Finally, our article provides an important bridge between the highly polarized criminological camps of masculinities and intersectionality and the psychoanalytic. It shows that multiple masculinities can be identified and they have a varied relationship with perpetration of violent and antisocial behavior and that these have origins in poverty, childhood trauma, and the enduring impact of this on men’s psyches.

Footnotes

Authors’ Note

The views expressed and information contained in it are not necessarily those of or endorsed by DFID, which can accept no responsibility for such views or information or for any reliance placed on them.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: UK Department for International Development (DFID), and grant was managed by their local partner Human Life Sciences Partnership (HLSP). Robert Morrell was assisted to participate in the project with funding from the National Research Foundation (NRF). This document is an output from the What Works to Prevent Violence: a Global Programme which is funded by the UK Aid from the DFID for the benefit of developing countries.

References

Abbey

Parkhill

M. R.

BeShears

Clinton-Sherrod

A. M.

Zawacki

2006. “Cross-sectional Predictors of Sexual Assault Perpetration in a Community Sample of Single African American and Caucasian Men.” Aggressive Behaviour 32:54–67.

Anderson

2009. Inclusive Masculinity. The Changing Nature of Masculinities. London, UK: Routledge.

Barker

Contreras

J. M.

Heilman

Singh

A. K.

Verma

R. K.

Nascimento

2011. Evolving Men: Initial Results from the International Men and Gender Equality Survey (IMAGES). Washington, DC: International Center for Research on Women.

Barker

Ricardo

Nascimento

2007. Engaging Men and Boys to Transform Gender-based Health Inequities: Is There Evidence of Impact? Geneva/Rio de Janiero: World Health Organization/Institute Promundo.

Beasley

2008. “Rethinking Hegemonic Masculinity in a Globalizing World.” Men and Masculinities 11:86–103.

Bernstein

Stein

J. A.

Newcomb

M. D.

Walker

Pogge

Ahluvalia

Stokes

Handelsman

Medrano

Desmond

Zule

2003. “Development and Validation of a Brief Screening Version of the Childhood Trauma Questionnaire.” Child Abuse & Neglect 27:169–90.

Bourgois

1996. “In Search of Masculinity: Violence, Respect and Sexuality among Puerto Rican Crack Dealers in East Harlem.” British Journal of Criminology 36:412–27.

Caspi

McClay

Moffitt

T. E.

Mill

Martin

Craig

I. W.

Taylor

Poulton

2002. “Role of Genotype in the Cycle of Violence in Maltreated Children.” Science 297:851–54.

Collier

1998. Masculinities, Crime and Criminology. Thousand Oaks, CA: Sage.

10.

Connell

1987. Gender and Power: Society, the Person and Sexual Politics. Palo Alta: University of California Press.

11.

Connell

R. W.

Messerschmidt

2005. “Hegemonic Masculinity: Rethinking the Concept.” Gender & Society 19:829–59.

12.

Contreras

Singh

Heilman

Barker

Verma

2011. “Connections between Early Childhood Experiences of Violence and Intimate Partner Violence.” Early Childhood Matters 116:26–32.

13.

Donaldson

1993. “What Is Hegemonic Masculinity?” Theory and Society 22:643–57.

14.

Dunkle

K. L.

Jewkes

Nduna

Jama

P. N.

Levin

J. B.

Sikweyiya

Koss

2007. “Transactional Sex and Economic Exchange with Partners among Young South African Men in the Rural Eastern Cape: Prevalence, Predictors, and Associations with Gender-based Violence.” Social Science & Medicine 65:1235–48.

15.

Dunkle

K. L.

Jewkes

R. K.

Brown

H. C.

Gray

G. E.

McIntryre

J. A.

Harlow

S. D.

2004. “Gender-based Violence, Relationship Power, and Risk of HIV Infection in Women Attending Antenatal Clinics in South Africa.” Lancet 363:1415–21. doi:10.1016/S0140-6736(04)16098-4.

16.

Dunkle

K. L.

Jewkes

R. K.

Nduna

Levin

Jama

Khuzwayo

Koss

M. P.

Duvvury

2006. “Perpetration of Partner Violence and HIV Risk Behaviour among Young Men in the Rural Eastern Cape, South Africa.” AIDS 20:2107–14. doi:10.1097/01.aids.0000247582.00826.52.

17.

Falk

Wallinius

Lundström

Frisell

Anckarsäter

Kerekes

2014. “The 1% of the Population Accountable for 63% of All Violent Crime Convictions.” Social Psychiatry and Psychiatric Epidemiology 49:559–71.

18.

Farrington

D. P.

Coid

J. W.

Harnett

L. M.

Jolliffe

Soteriou

Turner

R. E.

West

2006. Criminal Careers up to Age 50 and Life Success up to Age 48: New Findings from the Cambridge Study in Delinquent Development. London, UK: Home Office Research.

19.

Fonagy

Target

2003. Psychoanalytic Theories: Perspectives from Developmental Psychopathology. New York: Routledge.

20.

Frosh

Phoenix

Pattman

2002. “Taking a Stand: Using Psychoanalysis to Explore the Positioning of Subjects in Discourse.” British Journal of Social Psychology 42:39–53.

21.

Fulu

Jewkes

Roselli

Garcia-Moreno

2013. “Prevalence and Risk Factors for Male Perpetration of Intimate Partner Violence: Findings from the UN Multi-country Study on Men and Violence in Asia and the Pacific.” The Lancet Global Health 1:e187–207.

22.

Garcia-Moreno

Hansen

H. A.

Ellsberg

Heise

Watts

2005. WHO Multi-country Study on Women’s Health and Domestic Violence against Women. Geneva, Switzerland: World Health Organization.

23.

Herek

G. M.

1987. “On Heterosexual Masculinity: Some Psychological Consequences of the Social Construction of Gender and Sexuality.” In Changing Men: New Directions in Research on Men and Masculinity, edited by Kimmel

M. S.

, 365–74. Beverly Hills, CA: Sage.

24.

Hood-Williams

2001. “Gender, Masculinities and Crime: From Structures to Psyches.” Theoretical Criminology 5:37–60.

25.

Howson

2014. “Re-thinking Aspiration and Hegemonic Masculinity in Transnational.” Masculinities and Social Change 3:18–35.

26.

Jewkes

Dunkle

Koss

M. P.

Levin

J. B.

Nduna

Jama

Sikweyiya

2006. “Rape Perpetration by Young, Rural South African Men: Prevalence, Patterns and Risk Factors.” Social Science & Medicine 63:2949–61. doi:10.1016/j.socscimed.2006.07.027.

27.

Jewkes

Dunkle

Nduna

Jama

Puren

2010. “Associations between Childhood Adversity and Depression, Substance Abuse & HIV & HSV2 in Rural South African Youth.” Child Abuse and Neglect 34:833–41.

28.

Jewkes

Fulu

Roselli

Garcia-Moreno

2013. “Prevalence and Risk Factors for Non-partner Rape Perpetration: Findings from the UN Multi-country Cross-sectional Study on Men and Violence in Asia and the Pacific.” The Lancet Global Health 1:e208–18. doi:10.1016/S2214-109X(13)70069-X e1.

29.

Jewkes

Morrell

2010. “Gender and Sexuality: Emerging Perspectives from the Heterosexual Epidemic in South Africa and Implications for HIV Risk and Prevention.” Journal of the International AIDS Society 13:1–10.

30.

Jewkes

Morrell

Hearn

Lundqvist

Blackbeard

Lindegger

Quayle

Sikweyiya

Gottzen

2015. “Hegemonic Masculinity: Combining Theory and Practice in Gender Interventions.” Culture Health & Sexuality 17:112–27.

31.

Jewkes

Morrell

Sikweyiya

Dunkle

Penn-Kekana

2012a. “Men, Prostitution and the Provider Role: Understanding the Intersections of Economic Exchange, Sex, Crime and Violence in South Africa.” PLoS One 7:e40821. doi:10.1371/journal.pone.0040821.

32.

Jewkes

Morrell

Sikweyiya

Dunkle

Penn-Kekana

2012b. “Men, Sex and the Provider Role: Crime, Violence, Correlated Psychological Attributes Associated with South African Men’s Engagement in Prostitution and Transactional Sex in South Africa.” PLoS One 7:e40821. doi:10.1371/journal.pone.0040821.

33.

Jewkes

Morrell

Sikweyiya

Dunkle

Penn-Kekana

2012c. “Transactional Relationships and Sex with a Woman in Prostitution: Prevalence and Patterns in a Representative Sample of South African Men.” BMC Public Health 12:325. doi:10.1186/1471-2458-12-325.

34.

Jewkes

Nduna

Shai

Chirwa

Dunkle

. “Understanding the Relationships between Gender Inequitable Behaviours, Childhood Trauma and Socio-economic Status in Single and Multiple Perpetrator Rape in Rural South Africa: Structural Equation Modelling.” PLoS One.

35.

Jewkes

Sikweyiya

Morrell

Dunkle

2009. Understanding Men’s Health and Use of Violence: Interface of Rape and HIV in South Africa. Technical Report, Medical Research Council, Pretoria.

36.

Jewkes

Sikweyiya

Morrell

Dunkle

2011. “Gender Inequitable Masculinity and Sexual Entitlement in Rape Perpetration South Africa: Findings of a Cross-sectional Study.” PLoS One 6:e29590. doi:10.1371/journal.pone.0029590.

37.

Johansson

Santtila

Harlaar

von der Pahlen

Witting

Algars

Alanko

Jern

Varjonen

Sandnabba

N. K.

2008. “Genetic Effects on Male Sexual Coercion.” Aggressive Behaviour 34:190–202.

38.

Lilienfield

S. O.

2005. Psychopathic Personality Inventory—Revised. Lutz: Florida Psychological Assessment Resources.

39.

Lund

2008. Changing Social Policy: The Child Support Grant in South Africa. Cape Town, South Africa: HSRC Press.

40.

Makiwane

Udjo

2006. Is the Child Support Grant Associated with an Increase in Teenage Fertility in South Africa? Pretoria, South Africa: Human Sciences Research Council.

41.

Mathews

Jewkes

Abrahams

2011. “‘I had a Hard Life’’: Exploring Childhood Adversity in the Shaping of Masculinities among Men Who Killed an Intimate Partner in South Africa.” British Journal of Criminology 51:960–77.

42.

Messerschmidt

J. W.

1993. Masculinities and Crime: Critique and Reconceptualization of Theory. Lanham, MD: Rowman & Littlefield.

43.

Messerschmidt

J. W.

1997. Crime as Structured Action: Gender, Race, Class, and Crime in the Making. Thousand Oaks, CA: Sage.

44.

Messerschmidt

J. W.

2000. “Becoming ‘Real Men’: Adolescent Masculinity Challenges and Sexual Violence.” Men and Masculinities 2:286–307.

45.

Messerschmidt

J. W.

2012. “Engendering Gendered Knowledge: Assessing the Academic Appropriation of Hegemonic Masculinity.” Men and Masculinities 15:56–76.

46.

Morrell

Jewkes

Lindegger

Hamlall

2013. “Hegemonic Masculinity: Reviewing the Gendered Analysis of Men’s Power in South Africa.” South African Review of Sociology 44:3–21.

47.

Mullins

C. W.

2010. “Messerschmidt, James W: Masculinities and Crime.” In Encyclopedia of Criminological Theory, edited by Cullen

F. T.

Wilcox

, 620–624. Thousand Oaks, CA: Sage.

48.

Newburn

T.,

Stanko

E. A.

, Eds. 1994. Just Boys Doing Business?: Men, Masculinities and Crime. London, UK: Routledge.

49.

Pulerwitz

Barker

2008. “Measuring Attitudes toward Gender Norms among Young Men in Brazil: Development and Psychometric Evaluation of the GEM Scale.” Men and Masculinities 10:322–38.

50.

Pulerwitz

Gortmaker

DeJong

2000. “Measuring Sexual Relationship Power in HIV/STD Research.” Sex Roles 42:637–60.

51.

Sikweyiya

Jewkes

Morrell

2007. “Talking about Rape: Men’s Responses to Questions about Rape in a Research Environment in South Africa.” Agenda 74:48–57.

52.

Stouthamer-Loeber

Loeber

Homish

D. L.

Wei

2001. “Maltreatment of Boys and the Development of Disruptive and Delinquent Behavior.” Development and Psychopathology 13:941–55.

53.

Torbenfeldt Bengtsson

2015. “Performing Hypermasculinity: Experiences with Confined Young Offenders.” Men and Masculinities, 19: 410–428.

54.

Totten

2003. “Girlfriend Abuse as a Form of Masculinity Construction among Violent, Marginal Male Youth.” Men and Masculinities 6:70–92.

55.

Tremblay

Pagani-Kurtz

Massc

Vitaro

Pihl

R. O.

1995. “A Bi-model Prevention Intervention for Disruptive Kindergarten Boys: Its Impact through Mid-adolescence.” Journal of Consulting and Clinical Psychology 634:560–68.

56.

Walker

S. P.

Wachs

T. D.

Grantham-McGregor

Black

M. M.

Nelson

C. A.

Huff man

S. L.

Baker-Henningham

Chang

S. M.

Hamadani

J. D.

Lozoff

Meeks Gardner

J. M.

Powell

C. A.

Rahman

Richter

2011. “Inequality in Early Childhood: Risk and Protective Factors for Early Child Development.” The Lancet 378:1325–38.

57.

Whitehead

2002. Men and Masculinities: Key Themes and New Directions. Cambridge, MA: Polity.

58.

Wood

Jewkes

2001. “‘Dangerous’ Love: Reflections on Violence among Xhosa Township Youth.” In Changing Men in South Africa, edited by Morrell

, 317–36. Pietermaritzburg, South Africa: University of Natal Press.