A Gendered Look at Latinx General Strain Theory

Abstract

This study investigates gendered differences within Latinx experiences using a GST framework. We address four hypotheses: (1) Latinos and Latinas will vary in their degrees of risk for and resilience against criminal behavior; (2) Latinos and Latinas will experience strains to various degrees; (3) Latinos are more likely to respond to strain with violent and serious crime than Latinas due to the types of strains they face and their varying degrees of risk and resilience; and (4) ethnic identity will provide different degrees of resilience against violent and serious offending between Latinos and Latinas. Implications are discussed.

Keywords

general strain theory Latinxs gender ethnic identity risk resilience offending

While Latinxs currently represent approximately 18% of the United States (US) population (U.S. Census Bureau, 2019), they are projected to account for nearly 30% by 2060 (Stepler & Brown, 2016). More recently, research has begun to bring Latinxs to the forefront of criminological studies (e.g., Alvarez-Rivera et al., 2014; Isom Scott, 2018b, 2020; López & Pasko, 2017; Miller & Gibson, 2011); however, much of the scholarship still focuses exclusively on the differences between Blacks and Whites with very little attention on the effects for other people of Color (Schuck et al., 2004). Of the research that has focused on Latinxs, it has primarily centered on macro-level processes like the “Latino paradox¹,” acculturation, and assimilation (e.g., Cobb et al., 2017; Miller & Gibson, 2011; Sampson & Bean, 2006). As the Latinx population in the US continues to grow, scholarship must begin to examine the micro-level processes at work to understand how the lived experiences of Latinxs influence their criminal behavior and subsequent involvement in the criminal justice system. This is especially important given the structural, criminogenic conditions in which most Latinxs find themselves. More specifically, on average the Latinx population in the US is young, with low incomes and large families, and lives in underprivileged, urban communities (Malavé & Giordani, 2015). As a result, it is important that scholars theorize how Latinxs’ particular experiences influence their likelihood of offending.

Agnew’s (1992, 2006) general strain theory (GST) provides a framework for such group-specific analyses, as Agnew has long argued and research consistently finds strains operate differently—in form, reaction, and consequence—for various groups (e.g., Agnew & Brezina, 1997; Broidy, 2001; De Coster & Zito, 2010; Hay, 2003; Jang & Johnson, 2003; Mazerolle et al., 2003; Piquero & Sealock, 2010; Sigfusdottir et al., 2012). This, along with the calls from progressive scholars for inclusive theories and scholarship (e.g., Potter, 2015; Russell, 1992), inspired the articulations of gendered (Broidy & Agnew, 1997), racialized (Kaufman et al., 2008), and ethnically-specific (Pérez et al., 2008) versions of GST. Building on such work, Isom Scott and colleagues (2020) recently constructed and examined a revised version of Latinx general strain theory (LGST). While lending partial credence to LGST, Isom Scott et al. (2020) failed to capture the gendered variation within the Latinx² experience. The present work expands upon their recent analysis and applies a gendered assessment of LGST. In particular, employing the Project on Human Development in Chicago Neighborhoods (PHDCN) data (Earls et al., 2006, 2007a), we examine the distinct experiences of and responses to strains between Latinas and Latinos, thus bringing varied gendered realities forefront within the Latinx worldview.

General Strain Theory and the Latinx Experience

General strain theory (GST) posits that strain—the loss of something valuable, the failure to achieve a desired goal, and/or the presence of a noxious stimuli—leads to negative emotions like anger, depression, frustration, or anxiety. For those who lack conventionally appropriate coping skills to handle the resulting negative emotions, an individual may turn to criminal behavior as a means to alleviate the ensuing undesirable feelings (Agnew, 1992, 2006). Scholars have continuously found moderate empirical support for GST across a variety of samples and groups lending credibility to the theory’s generalizability (e.g., Agnew & Brezina, 1997; Broidy, 2001; Hay, 2003; Jang & Johnson, 2003; Mazerolle et al., 2003; Piquero & Sealock, 2010).

In addition to its empirical support, GST is the only leading theory in which scholars have put forth gendered and race-centric articulations of its arguments (i.e., Broidy & Agnew, 1997; Kaufman et al., 2008).³ In 2008, Pérez and colleagues developed an ethnic-specific version of GST that argued Latinxs experience discrimination and acculturation differently than other ethnic groups, which increases their likelihood of criminal behavior. In particular, Latinxs find themselves in a unique disjuncture between American norms and their cultural heritage (Denner & Guzmán, 2006; Rios, 2011; Wilkinson, 2003). Research has found that acculturation-related strains are associated with various adverse outcomes like depression (Cortés, 2003), psychological distress (Gong et al., 2003), substance use (Salas-Wright et al., 2015), as well as increased delinquency and involvement with the criminal justice system (Alvarez-Rivera et al., 2014; Cobb et al., 2017; Isom Scott et al., 2020; Pérez et al., 2008). Additionally, Latinxs often face significant discrimination particularly when seeking legal, medical, and social services (e.g., Bauer et al., 2000; Kasturirangan & Williams, 2003; Rodríguez et al., 2001), with some arguing that this unfair treatment stems not from factors such as skin color, language skills, or education, but rather from their presumed immigrant status (Malavé & Giordani, 2015).

Research suggests that Latinx youth, in particular, experience higher levels of depression and distress as a result of discrimination (Finch et al., 2000; Fisher et al., 2000) and, thus, may have different pathways to criminal behavior than their adult counterparts. Ultimately, the impact of acculturation and discrimination for Latinxs is empirically evident; yet, we still do not have a clear understanding of how the lived experiences of Latinxs in America affects their pathways into and potential resilience against crime. Thus, while research supports the need for investigation into the varied strainful experiences that theoretically disproportionately and distinctly impact Latinxs, extant literature has failed to acknowledge a driving factor of within group differences: gender.

Broidy and Agnew (1997) proposed women and girls experience different types of strains (e.g., more oppressive conditions, gender discrimination, excessive demands from family) that are experientially diverse compared to their male counterparts. Furthermore, Broidy and Agnew (1997) argued that men and women differ in their responses to strains. For example, women are more likely to respond to strain with a broader range of negative emotions such as fear, guilt, shame, and self-blame, and, in turn, cope with more inwardly self-directed harmful behaviors. Men, on the other hand, are more likely to respond to strain and anger with crime and other outwardly negative behaviors if they do not possess the necessary coping skills. Furthermore, these gender differences are largely rooted in heteronormative gender socialization, leading women and girls to be more likely passive and men and boys more aggressive. While research has empirically supported the various aspects of these gendered hypotheses (De Coster & Zito, 2010; Isom Scott & Mikell, 2019; Jang & Johnson, 2003; Piquero & Sealock, 2004), scholars need to further investigate the gendered responses to strain in conjunction with other statuses and identities, particularly race and ethnicity.

Gender and Ethnic Identity Within the Latinx Context

Of central import to understanding distinct group experiences is to understand how one’s group identity influences their perspectives and behaviors. Ethnic identity comprises a sense of pride and belonging about being a part of an ethnic group, along with providing a roadmap for traversing the bias, prejudice, and stereotypical beliefs embedded in American society (Phinney, 1992; Yancey et al., 2001). For some, ethnic identity instills resilience, for others resistance (e.g., Yancey et al., 2001). For Latinxs, a strong, positive ethnic identity is a mainstay of overall health and well-being (Yancey et al., 2001). It also mitigates the negative effects of discrimination (Martinez & Dukes, 1997) and victimization (Sabina et al., 2015). Yet, these effects often vary by gender (e.g., Chesin & Jeglic, 2012; Sabina et al., 2015). For instance, research suggests that a positive ethnic identity might serve as a greater protective barrier (i.e., reducing the likelihood of criminal involvement) for Latinas compared to Latinos (Chesin & Jeglic, 2012; Sabina et al., 2015). These disparities are largely rooted in the gendered dynamics of orthodox Latinx culture (e.g., Sanchez et al., 2019). Specifically, traditional Latinx families often socialize their children into idealized gender scripts of machismo and marianismo (Faulkner, 2003), with boys expected to be masculine and leaders of the household, while girls are taught to be submissive to men and virginally pure (Castillo & Cano, 2008; Galanti, 2003). Embedded within these notions is the concept of respeto, which emphasizes respect for the hierarchy of social relationships, particularly within families (Raffaelli & Ontai, 2004), and further positions Latinas as second-class citizens within orthodox Latinx culture.

In orthodox Latinx households, young Latinas are expected to play a supporting role in the family, showing deference to their fathers, brothers, and other male family members as well as supporting their mothers in household duties and childcare. Thus, they are taught to prioritize the family’s needs above their own (Ginorio et al., 1995; Sy & Romero, 2008). Beyond household duties, Latinas often feel obligated to provide financial support for the family as they enter adulthood (Sy & Romero, 2008). Many young Latinas feel their male counterparts are allotted more freedoms and less responsibilities than they are by their families (Sy & Romero, 2008). The ideals of marianismo have numerous negative effects for Latinas, such as increased negative emotions (Nuñez et al., 2016), particularly depression (Aranda et al., 2001; Céspedes & Huey, 2008), as well as acculturative stress (Ertl et al., 2018) and increased derogatory stereotyping (e.g., Guzmán & Valdiva, 2004; Medible, 2007; Vargas, 2010). The passivity imposed by marianismo often is associated with poor mental and physical health (Soto & Shaver, 1982). Latinas who resist the notions of marianismo often experience personal conflicts and stressors, particularly with their families (e.g., Castillo et al., 2015; Ertl et al., 2019; Schwartz et al., 2013; Sy & Romero, 2008). Furthermore, Latinas often cope with such stressors through drinking or engaging in sexual risk-taking behaviors (Kaplan et al., 2002; Perrotte et al., 2018).

While machismo allows more social freedoms and fewer domestic responsibilities for young Latinos, it also reinforces a toxic masculinity. Traditional cultural emphasis on domination and respect is associated with a limited emotional maturity, strained social relationships, and an increased likelihood of entanglements with and support for violence (Arciniega et al., 2008; Bratina, 2015; Nuñez et al., 2016; Saez et al., 2010; Sanchez et al., 2017), particularly for Latinos in more disadvantaged community environments (Williams et al., 2017). For Latinos, machismo is associated with higher levels of stress and depression (Fragoso & Kashubeck, 2000), greater intentions of risky sexual behavior (Perrotte et al., 2020), greater tolerance of dating violence attitudes (Terrazas-Carrillo & Sabina, 2019), lower overall well-being (Ojeda et al., 2016), and substance use (Gonzalez-Guarda et al., 2010).⁴ In general, Latinos are more likely to be aggressive and be less restrained against violence and criminal coping (Williams et al., 2017) than their Latina counterparts, who are more likely to be passive and prone to conforming behaviors (Lye & Waldron, 1998; Waldron & Lye, 1990). As such, then, gendered differences in traditional Latinx socialization and culture may influence one’s ethnic identity and in turn their ability to cope with the associated strains.

The Current Study

Due to the gendered nature of the Latinx experience reviewed above, it is highly likely the experience, response, and impact of strains will vary between Latinas and Latinos. In particular, we hypothesize the following:

H1: Latinos and Latinas will vary in their degrees of risk for and resilience against criminal behavior, particularly in terms of coping resources, social support, opportunities, social control, and disposition toward violent and serious offending, due to gendered orthodox cultural norms.

H2: Latinos and Latinas will experience strains to various degrees, with Latinos more likely to encounter strains conducive to violent and serious crime, such as negative encounters with the police and direct victimization, and Latinas more likely to encounter strains less conducive to violent and serious crime, such as less access to healthcare, financial burdens, and vicarious victimization.

H3: Latinos are more likely to respond to strain with violent and serious crime than Latinas due to the types of strains they face and their varying degrees of risk and resilience.

H4: Ethnic identity will provide different degrees of resilience against violent and serious offending between Latinos and Latinas due to the gendered nature of Latinx ethnic identity.

Our hypotheses align with the gendered notions of Broidy and Agnew (1997) and the ethnic-based propositions of Latinx GST (Isom Scott et al., 2020; also see Pérez et al., 2008) while accounting for the culturally-specific gendered nature of the Latinx experience. Below we assess these hypotheses using a subsample of Latinx youth from the PHDCN data (Earls et al., 2006, 2007a).

Method

Data and Sample

We use data from the third wave of the Longitudinal Cohort Study and the Community Survey of the PHDCN data (Earls et al., 2006, 2007a). The PHDCN is an interdisciplinary assessment that looks at the influence of urban communities, schools, and family situations on childhood, adolescent, and emerging adulthood development and antisocial behaviors. Data collection began in 1994 with Wave I of the Cohort Study and the Community Survey and finished in 2002 with Wave III. For the Community Survey, 343 neighborhood clusters were created from the 847 census tracts of Chicago, Illinois based upon the area’s socioeconomic status and racial and ethnic composition. The Longitudinal Cohort Study followed a stratified probability sample of 80 neighborhood clusters drawn from the original 343. Within each of these 80 neighborhood clusters, researchers sampled between 800 and 900 youth from each of the seven original age cohorts (i.e., birth, 3, 6, 9, 12, 15, and 18).

Our sample includes age cohorts 9, 12, 15, and 18 at Wave III, thus ranging in age from nearly 12 to 24 years old. We merged all relevant data files to the Wave III Personal Identity File (Earls et al., 2007b), which served as our base. One major strength of the PHDCN for this particular study is that it allowed respondents to self-report and rank their ethnic and racial identities. To identify the Latinx sample, we classified respondents as Latinx⁵ if they selected such as their sole or first identity in the categorical questions and/or listed it as their primary identity in the open-ended question. If their self-classifications did not match, the open-ended responses took precedence, yielding a final sample of 684 Latinxs. Missingness ranged from 0% to 44.2%.⁶ We analyzed the sample for systematic or randomly missing data patterns and replaced missing values using multiple imputation.⁷ We then split our final sample into gendered subsamples for analysis, composed of 349 Latina and 335 Latino youth, with mean ages of 17.8 and 17.4, respectively.

Measures

Dependent variable

Respondents were asked, “In the last year have you. . .” engaged in a variety of behaviors ranging from burglary to assault, with respondents providing a yes or no response to each of the twenty-three felony offenses. The final measure of serious and violent offending is a count outcome of how many types of offenses a person had engaged in over the last year.

Strains

LGST (Isom Scott et al., 2020) proposes Latinxs are more likely to experience ethnically-specific strains, as well as additional strains, due to their marginalized position in American society. For the ethnically-specific strains, we measured acculturative stress with the mean of two items: “it is hard getting along not speaking English well” and “it is hard at your job because of your poor English” (1 = never to 4 = always; α = .476).^8,9 We measured discrimination using the mean score of the following five items: in the past year were you discriminated against in your neighborhood, outside of your neighborhood, when you wanted service, when you first met someone new, or other times (1 = yes; α = .539). We measured police injustices using a single question asking whether or not the respondent had been discriminated by the police in the last year (1 = yes).

We also included additional strains as indicated by the prior literature. We measured lack of access to healthcare with the sum of three items: “Do [you] have a primary doctor?” (1 = no); “Where is the location of healthcare most often used?” (1 = none or other non-medical facility);” and “Did [you] ever lack health insurance since Wave II?” (1 = yes; all items recoded from the original). Higher scores indicated greater lack of access to healthcare. We gauged objective financial strain by the sum of eight items assessing negative financial situations during the past 6 months or year. Respondents were asked if they had experienced situations such as being unemployed, receiving welfare, not having enough food, or being evicted from their home (1 = yes). Higher responses indicated a higher level of objective financial strain. We captured subjective financial strain by the average of two questions: “How worried are you about not having enough money?”, and “How worried are you about not having enough money for the next 5 years?” (1 = not at all to 5 = extremely; α = .790). Direct victimization is a count measure of how many forms of threats and violence the subject experienced over the past year, including being attacked, shot, or sexually assaulted. Vicarious victimization is a yes or no 10-count measure of victimization indirectly experienced over the past year.

Conditioning variable

We adapted the measure of positive ethnic identity from the Puerto Rican Adolescent Survey (Earls et al., 2007b). Respondents were asked, “Please name the one ethnic or religious group that you think is most important to you.” Their answer served as the reference category for five items: “I tried to learn about (GROUP) history, traditions, and customs;” “I think a lot about how being (GROUP) has affected my life;” “I feel like a member of the (GROUP) community;” “I have often talked to other people to try to learn more about my (GROUP) culture;” and “I feel good about being (GROUP).” These items closely aligned with those from the Multigroup Ethnic Identity Measure—Revised (MEIM-R) (Phinney & Ong, 2007). Responses ranged from 1 = strongly disagree to 4 = strongly agree. If the respondent did not provide an ethnic or racial group as their most important group, the above questions were recoded to zero so the remaining responses would be ethnicity-based. We used the mean of the recoded responses as a measure of positive ethnic identity (α = .697).

Control variables

We included various control variables that are either known correlates of crime, are ethnically distinct controls, or are represented in leading criminological theories. Gender is a dichotomous variable with female coded as 1. Age is a continuous variable calculated from date of birth and the date of survey administration. Income is a categorical measure ranging from 1 = less than $5,000 annually to 11 = over $90,000 annually. We controlled for acculturation by a factor score of five items: proficiency in English; amount of English used daily; nativity to the US; US citizenship; and the degree one’s customs at home are American (α = .711).¹⁰ Higher scores indicated the respondent is more acculturated to the United States. We created a dichotomous indicator for those that self-identified Catholicism as a primary identity (1 = Catholic). Given sexuality is closely intertwined with orthodox Latinx gender norms (Deardorff et al., 2010; Faulkner, 2003; Isom Scott, 2018b), we measured sexual behavior by the sum of three items: “have you ever had sexual intercourse?;” “have you had more than one sexual partner?;” and “have you ever been pregnant/have you ever gotten someone pregnant?” (1 = yes). Higher scores indicated greater involvement in sexual behaviors.

We captured negative emotionality by the mean score of the questions, “I argue a lot;” “I scream a lot;” “I have a hot temper”; “I feel lonely;” “I cry a lot;” and “I am unhappy, sad, or depressed” with responses ranging from 0 = not true to 2 = very or often true (α = .600). Following Agnew (2013) and Thaxton and Agnew (2018), we created a criminal coping propensity index. Factors included were school enrollment, delinquent peers, low attachment to family, high impulsivity, and high risk-seeking tendencies. We recoded scales for each factor based on quartiles into dichotomous variables and summed with higher scores indicating a greater propensity for criminal coping.¹¹ Additionally, previous offending followed the same pattern as the dependent variable and captures all self-reported previous serious offending behaviors prior to Wave III.

Research finds community characteristics account for much of the disparity in crime rates (Bursik & Grasmick, 1993). We measured concentrated disadvantage, ethnic heterogeneity, and residential stability using indicators created by the original PHDCN investigators (Earls et al., 2007a; Sampson et al., 1997). Furthermore, given the theoretical emphasis on Latinx communities, we also controlled for percent Latinx in each neighborhood cluster.

Analytical Strategy

We employed a series of independent samples t-tests and negative binomial regressions for the present study. We provide standardized coefficients for ease of interpretation. The IRR provides the percentage change (determined by the difference between the IRR and one) in serious and violent offending for a one-unit change in the given factor controlling for all other covariates (Hilbe, 2011). The sample is nested within neighborhood clusters with varying degrees of disadvantage and stability. Stata15 allows for the control of clustering effects, thus providing robust standard errors (RSE) and conditional results that account for the nested nature of the data. Variance inflation factors (VIF) suggest none of the present measures suffer from multicollinearity. We cleaned the data using SPSS23 and finalized the analyses in Stata15. Descriptive statistics are presented in Table 1.¹²

Table 1.

Total Sample Descriptive Statistics (N = 684).

Variables	$\bar{x}$	SD	Minimum	Maximum
Serious and violent offending	.54	1.33	0	10
Acculturative stress	1.67	.66	1	4
Discrimination	.18	.23	0	1
Police injustices	.19	.39	0	1
Lack access to healthcare	.71	.82	0	3
Objective financial strain	.59	1.08	0	6
Subjective financial strain	2.44	1.11	1	5
Direct victimization	.37	.77	0	5
Vicarious victimization	2	1.96	0	10
Positive ethnic identity	.82	1.41	0	4
Controls
Gender (1 = female)	.51	.50	0	1
Age	17.62	3.62	11.75	24.36
Income	5.39	2.42	1	11
Acculturation	−.003	1.01	−2.15	2.36
Catholic	.10	.30	0	1
Sexual behavior	.87	1.05	0	3
Negative emotionality	1.10	.85	0	4
Criminal coping propensity	1.63	1.16	0	5
Previous offending	1.65	2.79	0	17
Concentrated disadvantage	−.07	.54	−1.13	2.66
Ethnic heterogeneity	1.12	.82	−1.39	3.07
Residential stability	−.33	.64	−1.99	1.75
Percent Latinx	.50	.26	0	.92

Results

The first hypothesis predicts Latinos and Latinas will vary in their degrees of risk for and resilience against criminal behavior. Table 2 presents the independent samples t-tests between Latinos and Latinas on the controls which capture elements of coping resources, social support, opportunities, social control, and disposition toward violent and serious offending. In line with gendered predictions, Latinos are significantly more likely to have engaged in previous serious offending than their Latina counterparts, and Latinas are significantly more likely to have higher negative emotionality. Furthermore, Latinas are significantly more likely to live in neighborhoods with greater ethnic diversity and Latinx populations. Latinos, on average, come from families with significantly higher incomes. While not statistically significant, Latinos have higher mean positive ethnic identity, higher American acculturation, stronger Catholic identity, and a greater propensity for criminal coping than Latinas. Latinas, surprisingly, reportedly engage in more sexual behavior on average than Latinos, though not significantly. Thus, hypothesis one finds only some support. While Latinas do experience some resilience factors more than Latinos, and Latinos do experience some risk factors at a higher rate than Latinas, neither are devoid of the other and many factors do not significantly vary across gender.

Table 2.

Differences in Risk and Resilience Factors by Gender.

	Female (n = 349)		Male (n = 335)		t	df
	$\bar{x}$	SD	$\bar{x}$	SD	t	df
Positive ethnic identity	.79	1.41	.86	1.41	.63	682
Age	17.8	3.60	17.4	3.63	−1.61	682
Income	5.21	2.43	5.59	2.40	2.07*	682
Acculturation	.01	1.00	−.02	1.03	−.42	682
Catholic	.09	.28	.11	.31	.82	682
Sexual behavior	.93	1.08	.82	1.01	−1.38	682
Negative emotionality^a	1.30	.93	.90	.70	−6.41**	644.58
Criminal coping propensity	1.58	1.17	1.68	1.14	1.09	682
Previous offending^a	1.14	2.16	2.18	3.24	4.91**	579.80
Concentrated disadvantage	−.07	.53	−.07	.55	−.10	682
Ethnic heterogeneity	1.21	.84	1.03	.80	−2.79**	682
Residential stability	−.32	.62	−.33	.67	−.29	682
Percent Latinx	.53	.26	.47	.25	−3.24**	682

Levene’s test for equality of variances finds equal variance cannot be assumed between females and males.

p < .05. **p < .01.

Hypothesis 2 predicts Latinos and Latinas will experience strains to various degrees, with Latinos more likely to encounter strains conducive to violent and serious crime, such as negative encounters with the police and direct victimization, and Latinas more likely to encounter strains less conducive to violent and serious crime like less access to healthcare, financial burdens, and vicarious victimization. Table 3 presents gender differences in experiences of strains. Independent samples t-tests reveal Latinos report experiencing significantly more police injustices, direct victimization, and vicarious victimization than their Latina counterparts, generally aligning with this hypothesis. While no other significant differences were revealed, Latinas did report higher mean levels of financial strains than Latinos. Thus, while Latinas and Latinos did not report experiencing different strains, and faced many of them to similar degrees, some gender differences did emerge, with Latinos being more likely to experience police injustices and victimization.

Table 3.

Differences in Experiences of Strain by Gender.

Strains	Female (n = 349)		Male (n = 335)		t	df
Strains	$\bar{x}$	SD	$\bar{x}$	SD	t	df
Acculturative stress	1.65	.70	1.70	.63	.81	682
Discrimination	.17	.22	.19	.23	.74	682
Police injustices^a	.13	.33	.26	.44	4.56**	620.70
Lack access to healthcare	.70	.82	.71	.83	.23	682
Objective financial strain	.62	1.09	.56	1.07	−.74	682
Subjective financial strain	2.51	1.15	2.36	1.07	−1.88	682
Direct victimization^a	.26	.61	.49	.90	3.82**	587.36
Vicarious victimization	1.77	1.84	2.24	2.06	3.10**	682

Levene’s test for equality of variances finds equal variance cannot be assumed between females and males.

p < .05. **p < .01.

Hypothesis 3 predicts Latinos are more likely to respond to strain with violent and serious crime than Latinas due to the types of strains they face and their varying degrees of risk and resilience. Table 4 presents the stepwise negative binomial regressions of ethnic strains, additional strains, and risk and resilience factors on serious and violent offending for the full sample, as well as for Latinas and Latinos independently. Such stepwise analysis allows for the assessment of confounding effects. Model 1 of Table 4 reveals the ethnic strains of discrimination and police injustices are significantly associated with an increase in serious and violent offending for Latinxs (IRR = 2.66 and 2.13, respectively). Yet, these associations are mitigated when additional strains are assessed in the model. Model 2 reveals direct and vicarious victimization are significantly associated, and objective financial strain is moderately significantly associated, with an increase in serious offending (IRR = 1.64, 1.41, and 1.13 [p = .059], respectively). Furthermore, subjective financial strain is significantly associated with a decrease in offending for Latinxs (IRR = .84). Again, however, these associations are further confounded when risk and resilience factors are controlled in the model. Model 3 reveals only direct and vicarious victimization remain significantly associated with serious offending (IRR = 1.45 and 1.27, respectively), in addition to gender, age, acculturation, sexual behavior, negative emotionality, and previous offending.

Table 4.

Negative Binomial Regression of Strains on Serious and Violent Offending.

	Full sample (N = 684)			Female (n = 349)			Male (n = 335)
	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6	Model 7	Model 8	Model 9
	IRR (RSE)	IRR (RSE)	IRR (RSE)	IRR (RSE)	IRR (RSE)	IRR (RSE)	IRR (RSE)	IRR (RSE)	IRR (RSE)
Acculturative stress^a	.93 (.15)	1.02 (.14)	1.07 (.15)	.62* (.13)	.64* (.12)	.70^† (.14)	1.01 (.18)	1.17 (.19)	1.25 (.20)
Discrimination	2.66* (1.12)	1.42 (.68)	1.17 (.47)	1.88 (1.31)	1.46 (1.07)	1.85 (1.36)	3.15* (1.51)	1.58 (.88)	1.09 (.61)
Police injustices	2.13** (.48)	1.04 (.27)	.73 (.17)	1.82 (.71)	.91 (.39)	.52^† (.21)	1.68* (.42)	.90 (.26)	.69 (.20)
Lack access to healthcare	—	1.07 (.12)	1.08 (.12)	—	.97 (.16)	1.28^† (.19)	—	1.13 (.15)	1.02 (.13)
Objective financial strain	—	1.13^† (.07)	1.04 (.07)	—	1.28* (.16)	1.04 (.12)	—	1.09 (.09)	1.03 (.09)
Subjective financial strain	—	.84* (.07)	.94 (.09)	—	.91 (.12)	1.01 (.17)	—	.85 (.09)	.93 (.11)
Direct victimization	—	1.64** (.13)	1.45** (.10)	—	1.38^† (.27)	1.56** (.22)	—	1.57** (.12)	1.49** (.12)
Vicarious victimization	—	1.41** (.05)	1.27** (.05)	—	1.59** (.12)	1.35** (.11)	—	1.33** (.06)	1.25** (.05)
Controls
Gender (1 = female)	—	—	.39** (.06)	—	—	—	—	—	—
Age^b	—	—	.90** (.03)	—	—	.78** (.05)	—	—	.98 (.04)
Income	—	—	.96 (.04)	—	—	.88^† (.07)	—	—	.99 (.06)
Acculturation	—	—	.85* (.07)	—	—	.78^† (.12)	—	—	.83 (.09)
Catholic	—	—	.55 (.31)	—	—	.37 (.31)	—	—	.66 (.42)
Sexual behavior	—	—	1.24* (.12)	—	—	1.67* (.36)	—	—	1.08 (.14)
Negative emotionality	—	—	1.31* (.14)	—	—	1.23 (.24)	—	—	1.37* (.18)
Criminal coping propensity	—	—	1.08 (.07)	—	—	1.11 (.14)	—	—	1.05 (.10)
Previous offending	—	—	1.17** (.04)	—	—	1.17** (.05)	—	—	1.15** (.05)
Concentrated disadvantage	—	—	.99 (.14)	—	—	.83 (.24)	—	—	1.05 (.16)
Ethnic heterogeneity	—	—	1.02 (.18)	—	—	1.46 (.43)	—	—	.94 (.20)
Residential stability^a	—	—	1.10 (.18)	—	—	2.09** (.46)	—	—	.87 (.15)
Percent Latinx	—	—	.71 (.38)	—	—	.29* (.18)	—	—	.90 (.65)
AIC	1,228.71	1,122.28	1,044.42	414.14	377.25	352.83	789.63	731.97	710.50
BIC	1,251.35	1,167.56	1,148.53	433.42	415.80	437.58	808.71	770.11	794.41
Log pseudolikelihood	−609.35	−551.14	−499.21	−202.07	−178.62	−154.42	−389.82	−355.98	−333.25

*p < .05 between the coefficients for females and males.

*p < .01 between the coefficients for females and males.

†

p < .10. *p < .05. **p < .01.

We repeated the stepwise regressions presented above on the Latina and Latino subsamples to better assess variations across gender. Model 4 of Table 4 reveals the ethnic strain of acculturative stress is significantly associated with a decrease in serious and violent offending for Latinas (IRR = .62), counter to predictions and previous literature. Furthermore, the other ethnic strains of discrimination and police injustices are not significantly associated with serious offending for Latinas. Model 5 finds the significant negative association for acculturative stress holds when other strains are included in the model. In addition, objective financial strain and vicarious victimization are significantly, and direct victimization is moderately significantly, associated with an increase in serious offending for Latinas (IRR = 1.28, 1.59, and 1.38 [p = .094], respectively). The gendered nature of the confounding effects of risk and resilience factors are displayed in Model 6. The associations between various strains and serious offending noticeably change when the controls are added to the model. Direct and vicarious victimization are both significantly associated with an increase in offending when risk and resilience factors are controlled (IRR = 1.56 and 1.35, respectively). Furthermore, acculturative stress and police injustices are moderately significantly associated with a decrease in serious offending (IRR = .70 [p = .065] and .52 [p = .099], respectively) while lacking access to healthcare is moderately associated with an increase in offending (IRR = 1.28 [p = .098]). Age, sexual behavior, previous offending, residential stability, and the percentage of Latinx in one’s community are significantly associated, and income and acculturation are moderately significantly associated, with serious offending for Latinas.

We find a very different pattern of associations for the Latino sample. Model 7 of Table 4 finds discrimination and police injustices are significantly associated with an increase in serious and violent offending for Latinos (IRR = 3.15 and 1.68, respectively). These associations, however, are mitigated when we assessed additional strains. Model 8 reveals only direct and vicarious victimization to be significantly associated with an increase in serious offending for Latinos (IRR = 1.57 and 1.33, respectively) when all strains are included in the model. Model 9 finds the significant associations between direct and vicarious victimization and offending generally hold when risk and resilience factors are controlled in the model (IRR = 1.49 and 1.25, respectively). Furthermore, negative emotionality and previous offending are the only additional significant factors revealed to be positively associated with increased offending for Latinos. Finally, following Paternoster et al. (1998), we analyzed z-scores between the Latina and Latino models to assess for significant differences in coefficients. Results are noted in Tables 4 and 5. The only significant differences revealed in Table 4 were between acculturative stress, age, and residential stability. Taken together, Table 4 lends modest support to our third hypothesis. While direct and vicarious victimization are significantly associated with increased serious offending for both Latinas and Latinos, the associations between other strains and risk and resilience factors varied greatly, though not always significantly, between Latinas and Latinos.

Table 5.

Negative Binomial Regression of Strains on Serious and Violent Offending.

	Full sample (N = 684)			Female (n = 349)			Male (n = 335)
	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6	Model 7	Model 8	Model 9
	IRR (RSE)	IRR (RSE)	IRR (RSE)	IRR (RSE)	IRR (RSE)	IRR (RSE)	IRR (RSE)	IRR (RSE)	IRR (RSE)
Acculturative stress	1.01 (.14)	.84 (.14)	.98 (.15)	.65* (.13)	.69^† (.15)	.75 (.18)	1.15 (.18)	.87 (.16)	1.07 (.17)
Discrimination	1.35 (.63)	1.56 (.74)	1.23 (.49)	1.36 (1.01)	1.92 (1.75)	1.38 (1.27)	1.52 (.81)	1.52 (.63)	1.16 (.46)
Police injustices	1.04 (.26)	.99 (.28)	.72 (.18)	.94 (.41)	.99 (.50)	.52 (.23)	.90 (.25)	.81 (.25)	.65 (.18)
Lack access to healthcare	1.10 (.11)	1.19 (.13)	1.21 (.15)	.98 (.15)	.97 (.18)	1.23 (.22)	1.16 (.15)	1.31^† (.19)	1.21 (.18)
Objective financial strain	1.14* (.07)	1.15^† (.09)	1.05 (.09)	1.28^† (.16)	1.23 (.21)	1.06 (.15)	1.10 (.10)	1.13 (.10)	1.07 (.11)
Subjective financial strain	.84* (.07)	.84^† (.07)	.95 (.09)	.91 (.12)	.96 (.15)	1.07 (.21)	.85 (.09)	.81* (.08)	.91 (.11)
Direct victimization	1.66** (.13)	1.79** (.20)	1.53** (.14)	1.40^† (.27)	1.48^† (.31)	1.59** (.25)	1.59** (.13)	1.69** (.21)	1.56** (.19)
Vicarious victimization	1.41** (.05)	1.34** (.07)	1.23** (.05)	1.58** (.12)	1.43** (.13)	1.30** (.12)	1.33** (.06)	1.31** (.07)	1.24** (.06)
Positive ethnic identity	1.10 (.08)	.63^† (.16)	.86 (.21)	1.08 (.10)	.85 (.31)	.84 (.29)	1.08 (.08)	.52* (.16)	.82 (.25)
Ethnic identity × acculturative stress	—	1.25* (.12)	1.13 (.11)	—	1.03 (.20)	.98 (.26)	—	1.36* (.16)	1.21^† (.14)
Ethnic identity × discrimination	—	.89 (.31)	.92 (.34)	—	.78 (.36)	1.30 (.68)	—	1.01 (.38)	.82 (.35)
Ethnic identity × police injustices	—	1.06 (.19)	1.02 (.18)	—	1.03 (.22)	1.17 (.24)	—	1.12 (.24)	.99 (.23)
Ethnic identity × lack access to healthcare	—	.85* (.07)	.85* (.06)	—	1.02 (.14)	.98 (.13)	—	.81* (.07)	.79** (.06)
Ethnic identity × objective financial strain	—	.99 (.06)	1.00 (.06)	—	1.03 (.11)	.99 (.08)	—	.97 (.07)	.94 (.10)
Ethnic identity × subjective financial strain	—	1.00 (.07)	.97 (.07)	—	.93 (.09)	.94 (.09)	—	1.08 (.08)	1.02 (.09)
Ethnic identity × direct victimization	—	.94 (.05)	.97 (.05)	—	.90 (.14)	.97 (.14)	—	.94 (.06)	.98 (.07)
Ethnic identity × vicarious victimization	—	1.13* (.05)	1.07 (.05)	—	1.16** (.06)	1.10 (.06)	—	1.07 (.07)	1.06 (.06)
Controls
Gender (1 = female)	—	—	.40** (.06)	—	—	—	—	—	—
Age^b	—	—	.92* (.04)	—	—	.78** (.05)	—	—	1.00 (.05)
Income	—	—	.96 (.04)	—	—	.90 (.07)	—	—	1.00 (.05)
Acculturation	—	—	.85^† (.07)	—	—	.77 (.12)	—	—	.84 (.09)
Catholic	—	—	.60 (.33)	—	—	.34 (.28)	—	—	.80 (.52)
Sexual behavior	—	—	1.19^† (.12)	—	—	1.66* (.37)	—	—	1.01 (.13)
Negative emotionality	—	—	1.33* (.15)	—	—	1.18 (.24)	—	—	1.50** (.22)
Criminal coping propensity	—	—	1.07 (.07)	—	—	1.07 (.14)	—	—	1.06 (.11)
Previous offending	—	—	1.17** (.04)	—	—	1.18** (.06)	—	—	1.14** (.04)
Concentrated disadvantage	—	—	1.02 (.14)	—	—	.80 (.28)	—	—	1.11 (.15)
Ethnic heterogeneity	—	—	1.00 (.19)	—	—	1.48 (.43)	—	—	.85 (.19)
Residential stability^a	—	—	1.07 (.17)	—	—	2.14** (.50)	—	—	.83 (.14)
Percent Latinx	—	—	.65 (.36)	—	—	.30^† (.22)	—	—	.90 (.66)
AIC	1,121.67	1,123.36	1,052.92	378.74	390.03	366.80	732.96	735.64	716.70
BIC	1,171.48	1,209.40	1,197.77	421.15	463.28	486.22	774.91	808.10	834.94
Log pseudolikelihood	−549.83	−542.68	−494.46	−178.37	−176.02	−152.40	−355.48	−348.82	−327.35

*p < .05 between the coefficients for females and males.

*p < .01 between the coefficients for females and males.

†

p < .10. *p < .05. **p < .01.

The final hypothesis predicts positive ethnic identity will provide different degrees of resilience against violent and serious offending between Latinos and Latinas due to the gendered nature of Latinx ethnic identity. Table 5 follows the same general pattern as the stepwise regressions above, first assessing the direct association of positive ethnic identity, then the conditioning effects of ethnic identity on the experience of strains,¹³ and finally the confounding effects of risk and resilience factors on these conditioning effects for the full sample as well as for Latinas and Latinos independently. Model 1 of Table 5 finds positive ethnic identity is not directly associated with serious and violent offending for Latinxs. Model 2 finds positive ethnic identity significantly conditions the associations between acculturative stress, lacking access to healthcare, and vicarious victimization and serious offending. However, this conditioning effect only remains for lacking access to healthcare when risk and resilience factors are included in Model 3.

Models 4 through 9 of Table 5 present the gendered assessments of these conditioned associations. Model 4 reveals positive ethnic identity is not significantly associated with serious offending for Latinas. Model 5 finds positive ethnic identity significantly conditions the association between vicarious victimization and offending for Latinas. However, Model 6 reveals this conditioning effect is mitigated by risk and resilience factors.

For Latinos, again positive ethnic identity is not directly associated with serious and violent offending as revealed in Model 7. Model 8, however, finds positive ethnic identity does significantly condition the associations between acculturative stress and lacking access to healthcare and serious offending for Latinos, and these effects generally hold when risk and resilience factors are included in Model 9.

Additional analyses, however, are warranted to decipher these significant interaction effects. A subcommand in Stata provides the IRR for each level of ethnic identity in conjunction with the significantly conditioned strain holding other covariates constant. The multiplicative effects revealed in Models 2, 5, and 8 are plotted in Figures 1 to 6.¹⁴ Figures 1 to 3 reveal holding a positive ethnic identity significantly mitigates the association between acculturative stress, lacking access to healthcare, and vicarious victimization with serious offending for Latinxs. Figures 4 to 6 reveal the gendered nature of these associations. Figure 4 finds the mitigating effects of positive ethnic identity to only be associated with vicarious victimization for Latinas. And, Figures 5 and 6 reveal holding a positive ethnic identity only abates the associations between acculturative stress and lacking access to healthcare for Latinos. Yet, overall, the moderate slopes revealed also suggest holding a positive ethnic identity is not a strong protective factor generally against strainful experiences. Thus, again our results provide only modest support for our final hypothesis, as holding a positive ethnic identity does operate differently between Latinas and Latinos, but only provides modest resilience, if any at all, to either and in varied ways.

Figure 1.

Significant conditioning effect for total sample—acculturative stress.

Figure 2.

Significant conditioning effect for total sample—limited access to healthcare.

Figure 3.

Significant conditioning effect for total sample—vicarious victimization.

Figure 4.

Significant conditioning effect for females—vicarious victimization.

Figure 5.

Significant conditioning effect for males—acculturative stress.

Figure 6.

Significant conditioning effect for males—limited access to healthcare.

Discussion

The overall aim of this study was to investigate gendered differences within Latinx experiences using a GST framework. In particular, we addressed four GST-grounded gendered hypotheses: (1) Latinos and Latinas will vary in their degrees of risk for and resilience against criminal behavior, particularly in terms of coping resources, social support, opportunities, social control, and disposition toward violent and serious offending, due to gendered orthodox cultural norms; (2) Latinos and Latinas will experience strains to various degrees, with Latinos more likely to encounter strains conducive to violent and serious crime, such as negative encounters with the police and direct victimization, and Latinas more likely to encounter strains less conducive to violent and serious crime, such as less access to healthcare, financial burdens, and vicarious victimization; (3) Latinos are more likely to respond to strain with violent and serious crime than Latinas due to the types of strains they face and their varying degrees of risk and resilience; and (4) Ethnic identity will provide different degrees of resilience against violent and serious offending between Latinos and Latinas due to the gendered nature of Latinx ethnic identity. While not as clearly distinct as hypothesized, our results find Latinas and Latinos do experience and respond to strains differently and a positive ethnic identity does operate markedly across gender. Yet, our results also reveal many similarities and complexities for Latinx youth.

The race and ethnicity literature find people of Color, particularly Blacks and Latinxs, face distinct and disproportionate strains, including discrimination, police injustices, victimization, educational and occupational barriers, economic hurdles, healthcare inequities, and family dysfunction (Cobbina, 2019; Dovidio et al., 2010; Kaufman et al., 2008; Pérez-Escamilla, 2010; Rios, 2007, 2009; Unnever & Gabbidon, 2011; Yearby, 2018). Furthermore, men and boys of Color are more likely to face harassment from the police (García, 2013) whereas women and girls of Color are more vulnerable to direct and vicarious victimization (Isom Scott, 2018a; West & Johnson, 2013) compared to their gendered and racial/ethnic counterparts. Our findings generally align with these notions, finding both Latina and Latino youth experience all forms of the assessed strains—acculturative stress, discrimination, police injustices, financial hardship, limited access to healthcare, and victimization—but to various degrees. Latinos experienced significantly greater degrees of police injustices as well as vicarious and direct victimization than their female counterparts. This is likely due to young men spending more time in public in social groups, exposing themselves to the eyes of the police as well as opportunities for violence (e.g., Rios, 2011), than their female counterparts. Furthermore, counter to Broidy and Agnew’s (1997) gendered predictions, Latinas reported more subjective financial strain than their male counterparts. This may be a cultural difference as Latina girls are traditionally socialized to be virtuous, humble, and family-oriented (Castillo & Cano, 2008; Galanti, 2003), and thus reflects a concern for their ability to take care of social obligations (Ginorio et al., 1995; Sy & Romero, 2008). While unpacking fully why Latina and Latino youth experience different strains is beyond the present scope, our findings highlight that differences do exist and are, therefore, worthy of further investigation.

Of particular importance are the various significant associations between ethnically-specific and other strains on offending between Latina and Latino youth. For instance, despite both Latinas and Latinos reporting experiencing discrimination and police injustices, such experiences were only significantly associated with offending for Latinos. Furthermore, the predictive power of discrimination and police injustices disappears when other strains beyond ethnically-specific negative encounters were considered, and direct victimization (along with vicarious victimization for Latinos) became the primary drivers of offending. These associations align with our gendered predictions that Latinos are more likely to cope with such strainful encounters with violence and other-directed crime than their Latina counterparts, particularly given the ideals of machismo and potentially demonstrating toughness through aggression and violence. Furthermore, while discrimination and police injustices were impactful, such experiences were not significantly associated with serious offending when Latinos experienced victimization either directly or indirectly. On the surface these results are surprising. However, the experiences of discrimination and injustices may be so commonplace for Latinos they have learned to cope with such chronic encounters, much like their Black counterparts (e.g., Brown & Tylka, 2011; Mallett & Swim, 2009). Additionally, the objective and subjective judgements of these strainful experiences may influence their varied associations (Agnew, 2006). While beyond the present scope, we believe that there should be further empirical investigation into the distinctions between chronic and acute, as well as objective and subjective, strainful experiences for Latinos, in addition to further investigation into how such experiences are gendered.

More surprisingly, however, is the negative significant association between acculturative stress and serious offending for Latinas. This counters extant literature that finds acculturative strains are associated with a gamut of negative outcomes from depression (Cortés, 2003) and psychological distress (Gong et al., 2003) to delinquency and involvement with the criminal justice system (Alvarez-Rivera et al., 2014; Cobb et al., 2017). However, this also emphasizes the multifaced nature of acculturation and acculturative stress. Familial, cultural, or internal tensions from embracing American culture may not arise for all. The significance of acculturation and in turn acculturative stress varies between newly immigrated individuals, first-generation Latinxs, and multi-generation Latinx Americans (e.g., Bersani, 2014; Bersani & Piquero, 2017). If a household is bilingual and American and Latinx customs are equally adopted, then one may not feel torn between cultural identities (Good et al., 2010). Furthermore, acculturative stress may vary generationally as adults more so than youth try to maintain connections to their ethnic culture and family roots (e.g., Williams et al., 2017). Moreover, the negative association revealed presently is most likely tied to gender and the measure itself. Our measure exclusively captures stress associated with language skills and navigating society. While such strains have been associated with stress for Latinx individuals regardless of nativity (Vega et al., 1995), it fails to capture the varied social, familial, and cultural experiences that could lead to acculturative stress. Furthermore, orthodox Latinx culture highly restricts Latinas’ engagement with non-familial others and opportunities to partake in serious offending. Thus, stress associated with limited English-language skills may be associated with other forms of deviant coping for Latinas, but not serious offending. Though beyond the present scope, these supposed generational and familial differences, as well as gendered disparities, warrant further investigation into the varied effects of acculturation and resulting distress.

Furthermore, our results lend some evidence to the gendered differences in risks and resilience factors. Again, these differences are likely rooted in cultural gender socialization (Faulkner, 2003; Jennings et al., 2009; Ornelas & Hong, 2012) as well as gendered differences in lived experiences in our patriarchal society (Broidy & Agnew, 1997; Isom Scott, 2018b). For instance, the ideals of family are largely rooted in community in traditional Latinx culture (Cardoso & Thompson, 2010; Cauce & Domenech-Rodriguez, 2002), particularly in the norms of protecting daughters and their purity. Thus, Latina youth are often placed under more social control by their households as well as community compared to their male counterparts (Galanti, 2003; Raffaelli & Ontai, 2004). These gendered norms likely account for why living amongst a large Latinx population protects Latinas from offending but is not significant for Latinos. And relatedly, such controls can result in the opposite of intended effects, leading young women to rebel against authority, or too much control, and engage in deviant behavior (e.g., Scheuerman et al., 2019), which is likely reflected in the significant associations between sexual behavior and residential stability and offending for Latinas but not their male counterparts.

Finally, of central importance to our gendered analysis is the varied effects of ethnic identity. The research is mixed on the role of ethnic identity with some suggesting that a positive ethnic identity protects one from the negative effects of discrimination for Latinxs (Martinez & Dukes, 1997) and other studies finding null effects (Arbona et al., 1999; Isom Scott, 2020). Our findings suggest these varied effects may be rooted in gender, as positive ethnic identity only partially mitigates the associations between varied strains and serious offending for Latinas and Latinos. In particular, a positive ethnic identity provided some resilience against vicarious victimization for Latinas, but no other strainful experiences. Furthermore, it mitigated the association between acculturative stress and limited access to healthcare for Latinos, but neither were directly associated with serious offending. Moreover, the varied impact of risk and resilience factors between Latinas and Latinos, particularly when considering the conditioning effects of positive ethnic identity, speak to the gendered complexities between Latina and Latino lived experiences. Yet again, as previously noted, the very modest slopes revealed here suggest ethnic identity as captured presently only provides very slight resilience against strainful experiences at best. While unpacking these gendered effects are beyond the abilities of the present data, our results do support the intricate relationship between gender and ethnicity for Latinxs and future research is warranted to investigate the nature and impact of these complexities.

Limitations

While we find partial support for our hypotheses, as with all research, our study has some limitations. First, secondary data has several weaknesses. The first limitation is the quality of the available measures, such as our measure of acculturative stress, as noted above. The discrimination variable, also, fails to capture the full array of discriminatory experiences one may have, for instance when applying for a loan or a job among others. Additionally, our measure of police injustices is based on a single question. Again, as with our measure of discrimination, this does not fully gauge the breadth and depth of such encounters. Along the same lines, definitions of discrimination as well as the measures used in empirical work vary greatly, leading scholars to call for more consistency (Kressin et al., 2008). Ultimately, the measures of discrimination and injustices presented in this study are conservative at best. Additionally, Agnew (2006) outlines the role of trait negative emotionality, as currently captured, compared to the state emotional responses to strain in GST. Furthermore, Broidy and Agnew (1997) clearly argue for gendered variations in emotionality and emotional responses to strain. Thus, future work should further examine the intricacies of anger and depression, both as a state and a trait, while also assessing the role of other negative emotions like frustration, guilt, or sadness. Scholars should also consider other potential culturally specific positive coping strategies like intramural, extracurricular sports (e.g., Marsh & Kleitman, 2003; Pfeifer & Cornelissen, 2010). It is possible that these additional emotions and coping resources highlight often hidden relationships between strain and crime for Latinxs.

Furthermore, the current sample includes anyone who self-identified as Mexican, Central and South American, and Spanish-speaking Caribbean. Despite similarities, there are also substantive ethnic and cultural differences (Cuevas et al., 2014). Future research must examine disparities across country of origin to determine similarities and differences in experiences and behaviors. Additionally, to better gauge gender differences, gender identity, gender socialization, and ethnically-specific gender socialization need to be assessed. For a Latinx context, utilization of measures such as the Marianismo Beliefs Scale (Castillo et al., 2010) is warranted to capture internalized orthodox norms. Furthermore, we must push back against the gender binary. There are numerous masculinities and femininities within society that vary based on time, culture, context, and the physical embodiment of the one living the experience (Connell, 1987; Messerschmidt, 2000, 2004; Weitz, 1977). Developing ways to better capture such intricate experiences is needed to better understand the myriad influences of gender. We also only examined one form of criminal outcomes—serious and violent offending. It is plausible culturally specific stressors may be associated with other deviant and negative, albeit not necessarily criminal, outcomes, such as drug use, self-harm, or less serious criminal actions like property offenses, particularly across gender. Additional research into these associations is needed.

Furthermore, at time of authorship the PHDCN is nearly 20 years old. Significant culture shifts have occurred over the last two decades, including a moral panic around immigration leading to the formation of a crimmigration system (Hernández, 2013) and a significant rise in hate crimes against Latinxs (Brooks, 2019). The threat of deportation is a very real and apparent strain on the lives of most Latinx folks, including Latinx Americans. While the present work is a start to understanding Latinxs’ distinct pathways to and resilience against offending, additional theoretical and empirical work are needed to more fully capture the Latinx experience within the current American climate. Lastly, the present data are cross-sectional. Future studies should use longitudinal data in order to assess causal order as well as any mediating and/or moderating effects.

In sum, taken together these results support the need for critical intersectional scholarship to investigate within variations and complexities among different groups. The present findings lend credence to the fact Latina and Latino youth experience and respond to strains differently, and these differences are likely rooted in culturally gendered messages and resultant ethnic identities. We call on scholars to continue to investigate these contexts and complexities to best inform culturally competent reforms and policies.

Footnotes

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) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Deena A. Isom

Notes

Author Biographies

Deena A. Isom is an assistant professor in the Department of Criminology & Criminal Justice and African American Studies Program at the University of South Carolina. Her scholarly agenda broadly aims to bring marginalized and oft-forgotten experiences and voices forefront in the understanding of criminal behavior and contact with the justice system. Her work has appeared in outlets such as the Journal of Criminal Justice, Journal of Contemporary Criminal Justice, Race and Justice, Youth & Society, and Deviant Behavior.

Jessica M. Grosholz is an associate professor of Criminology in the College of Liberal Arts and Social Sciences at the University of South Florida Sarasota-Manatee. Her research interests include assessing criminological theories, health and crime, and the prison experience. Her research has appeared in the Journal of Criminal Justice, Social Science and Medicine, Youth & Society, and Deviant Behavior, among others.

Serita Whiting is a doctoral candidate at Prairie View A&M University. Her research interests include criminological theory, mass incarceration, and juvenile delinquency.

Tylor Beck is a doctoral student at the University of South Carolina. Her research interests include veteran incarceration, police handling of emotionally disturbed persons, sentencing reform, rehabilitation and alternative sentencing to incarceration.

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