(SCI) Journals in Social Science

1403/9/11 00:26

(SCI) Journals in Social Science

](SCI) Journals in Social Science

The effect of unhealthy family relationships on the spread of delinquency with a look at the laws of the United States

Dr. Hesamoddin Rahimi

Law professor at Tehran University

Haftaseman7777@gmail.com

http://dx.doi.org/30.1916/j.ins.2022.09.013 

Abstract

The structure and stability of families have long stood as key predictors of juvenile delinquency. Boys from “broken homes” experience a higher prevalence of juvenile delinquency than those from intact families (Rebellon 2002, Wells and Rankin 1991). Unresolved is whether the consequences of frequently disrupted family contexts endure to shape criminal trajectories into adulthood. Long-term influence may also be indirect. Life course criminologists credit family formation during the transition to adulthood, and particularly marriage, for redirecting men’s criminal trajectories, but children who experience repeated changes in family structure are more likely to experience precarious starts to their own eventual family formation. Using data from the Panel Study of Income Dynamics and its two child-centered supplemental studies (N=1,127), we find that the experience of repeated family structure change is associated with higher rates of arrest and incarceration during early adulthood for white men but not for black men. This association is partially mediated by a slower transition to marriage among men who experienced three or more changes in family structure during childhood.

Introduction

The study of criminal behavior once centered on juvenile delinquency. In the absence of longer-running longitudinal data, much research focused cross-sectionally on the teenage years – a portion of the life course during which criminal behavior peaks. The family thus played an important role in understanding youthful offending. Criminologists have argued that an assortment of characteristics ranging from the size of the family to parents’ childrearing methods matter (Farrington 2011). No characteristic has been as extensively researched as family structure, however (Wells and Rankin 1991). Popularized by Bowlby’s (1951) World Health Organization report, the conclusion that “broken homes” cause crime has been a sturdy one. Meta-analyses consistently find that children who are raised in homes in which at least one biological parent is absent face a higher prevalence of adolescent delinquency (Rebellon 2002, Wells and Rankin 1991).

With the maturation of life course studies, criminological attention has moved beyond the teenage years to understand criminal behavior over the entire life course. In particular, criminologists have sought to explain why some offenders persist in, while other offenders desist from criminal activity as they enter adulthood. Again, the role of the family has emerged as pivotal in steering criminal trajectories. Life course criminologists contend that marriage, in particular, has the potential to serve as a turning point, redirecting criminal trajectories (Laub and Sampson 2006, Sampson and Laub 1995).

Yet for all of their emphasis on the long view of criminal behavior, life-course criminologists have been relatively short-sighted in their view of the family. We know little about whether childhood family experiences endure to impact adult criminal outcomes. Moreover, there is an increasing awareness of the ways childhood family instability undermines transition to adulthood experiences including one’s own family formation (Fomby and Bosick 2013Hofferth and Goldscheider 2010). This suggests that if early family instability does not directly contribute to adulthood criminality, it may fuel adult crime by undermining the transition-to-adulthood experiences that might otherwise curtail it.

In this paper we use the long-running US Panel Study of Income Dynamics (PSID) and its two child-centered supplements, which have followed a nationally-representative cohort of youth since 1997 to early adulthood in 2015, to ask whether the experience of repeated changes in mother’s union status during childhood are predictive of men’s higher likelihood of arrest or incarceration during early adulthood (ages 18–26). Furthermore, we consider whether any such association is mediated by differences in the pace of men’s entry into marriage and their higher risk of union dissolution depending on prior exposure to maternal union instability. We consider whether these pathways operate differently for white and black men, an expectation based on research demonstrating that frequent family instability is less consequential for the life course of trajectories of black compared to white young adults (Fomby, Mollborn and Sennott 2010).

Literature review

The life course literature has long acknowledged the role of family formation in redirecting criminal paths. Men who as juveniles were involved in crime and delinquency are less likely to persist in criminal involvement if and when they become married (Sampson and Laub 1995). Criminally active men who remain single are, in contrast, more likely to continue offending well into adulthood. Increasingly, scholars have sought to contend with the complicated lived experiences that render modern family life more complex and varied than in the past, including divorce, cohabitation, nonresidential parenthood, and multipartner fertility. Findings consistently indicate that cohabitation is related to desistance, but its not as strongly associated as marriage (Forrest 2014). Moreover, men who experience divorce or separation experience upticks in their criminal activity, particularly when not living with a spouse (Horney, Osgood and Marshall 1995). Work focusing on the association between parenthood and offending has arrived at less consistent findings, though men’s desistance generally appears to be unmotivated by fatherhood (Blokland and Nieuwbeerta 2005).

There is an increasing tension hinted at when the work in this area calls out analyses for using “old” data. What feels antiquated may not be the data itself. After all, longitudinal and life course researchers appreciate that the aging of data is inherent to prospective longitudinal data. More problematic is that the idea of stable marriage grows increasingly antiquated, especially in contexts in which criminal behavior is most likely. The median age at first marriage for women has increased from 24 in 1990 to 27 today. Black Americans marry at lower rates than whites in every age group, and particularly so during their late twenties, when 115.6 out of every 1000 white women but only 43 out of every 1000 black women marry (Aughinbaugh, Robles and Sun 2013, Raley, Sweeney and Wondra 2015). Thus the argument that marriage causes desistance strikes a conservative chord, and is ill-matched to the most problematic offenders who are unlikely to marry at rates similar as offenders who transitioned to adulthood in decades past (Sampson and Laub 1995).

The evolving historical context of marriage reinforces the selection processes that have hampered causal claims about the effect of marriage on criminal outcomes. Clearly, marriage is not randomly assigned; there are forces shaping who becomes married and who does not. Sampson and colleagues (2006) addressed selection issues using a counterfactual approach and found continued support for a marriage effect. That marriage remains effectual is important. Still, we contend that it is also important to understand the selection processes themselves.

The family literature recognizes the impact of repeated family structure change on the children who experience it. Above and beyond having been raised in a single-parent household, or having experienced parental divorce, experiencing family instability appears to undermine educational outcomes, problematizes one’s transition to adulthood, and contributes to risky and delinquent behavior (Fomby and Cherlin 2007Fomby et al. 2010Fomby 2013Fomby and Bosick 2013Lee and McLanahan 2015, Wu and Martinson 1993). The extent to which these setbacks persist into adulthood is less clear.

Static theories of criminal persistence suggest a direct route from early disadvantages that would include family instability to later criminal behavior. On the other hand, early family instability may produce problems in adulthood through a process of cumulative disadvantage. “Dynamic” theories recognize that setbacks accumulate throughout the life course and grant a causal connection between earlier and later problems (Sampson and Laub 1997). Early family instability is associated with disrupted transition to adulthood experiences of the children who experience it. Thus, early family instability may influence adult offending indirectly by disrupting the very transitional experiences thought to curtail criminal behavior.

This paper advances the literature by taking a longer view of the role of family on criminal outcomes in adulthood. We bring a dynamic measure of family instability to the criminological literature in order to understand whether the association between early family instability and misbehavior persists into adulthood, and whether this association is mediated by men’s own family formation experiences.

Further, we consider whether this approach is equally useful for describing the probability of offending in early adulthood among non-Hispanic white and black men. A substantial literature has demonstrated that family instability is more strongly associated with externalizing behavior, delinquency, and early transition to adulthood experiences among white adolescents and young adults compared to their black peers. Little research has sought to explain racial differences in the influence of union instability on behavior, but some research suggests that black youth may have more social protection through enduring relationships with extended kin, neighbors, and peers following family disruption compared to white adolescents; there is also some evidence that economic stress may overwhelm the effects of repeated family structure change on behavior, and economic stress occurs more often in black compared to white families (Fomby et al. 2010). Given the disproportionately high incarceration rates among black young adults in the United States and the popular perception that family structure in black children’s families plays a causal role in criminal behavior leading to arrest and incarceration, it would be an important contribution to demonstrate the absence of any such association if none is present.

Methodological background

Cross-sectional studies characteristically struggle to establish temporal order, making causal connections difficult to infer. Mature longitudinal studies more successfully track the temporal order of life events, but leave researchers the task of capturing this order in their analysis.

To capture the diverse experiences navigating the transition to adulthood period, researchers have employed methods including latent class analysis (e.g. Macmillan and Eliason 2003, Osgood, Ruth, Eccles et al. 2005) and conjunctive analysis of case configurations (Doherty and Cwick 2016). These methods allow researchers to identify and describe the most typical role configurations and summarize the typical pathways through adulthood. These strategies are useful in describing conceptually related events in the life course. Analyses become more complicated as they move toward establishing causal order between life experiences.

The most straightforward analyses are those which examine experiences in one period of life on experiences in later life. Macmillan’s (Macmillan and Hagan 2004) use of the National Youth Survey to identify a “chain-like” sequence in which victimization experienced in adolescence diminishes educational self-efficacy at 18, which ultimately undermines socioeconomic attainment in early adulthood. In studies of the relationship between transition-to-adulthood experiences and crime, researchers recognize that these events and behaviors are occurring simultaneously. In order to sort out sequence, some impose temporal order by censoring the data into distinct age periods. Bosick (2015), for instance, dodges the issue of overlapping events by modeling transition-to-adulthood in early adulthood and examining the association between these pathways and later adulthood crime.

Other strategies include modeling risky and criminal behavior as part of the transition to adulthood, where both transitional experiences and criminal activity are simultaneously taken as indicators of a latent construct (Massoglia and Uggen 2010). Uggen and Janikula (Uggen and Janikula 1999) have used event history analysis to capture how time-varying voluntary labor experiences influence the duration until arrest. Similarly, Uggen (2000) tests for job-treatment effects by randomly assigning over 3,000 people with arrest histories to either a control or treatment group. He use an event history approach in order to aid in determining the sequence of work and criminal behavior. Horney, et al (Horney et al. 1995) use hierarchical linear modeling to capture the month-to-month impact of life circumstances (e.g. living with a romantic partner) on criminal behavior.

Results

Table 1 summarizes weighted descriptive statistics for the dependent variables, key variables of interest, and control variables overall and by race from the person-year file. Statistically significant group differences by race (p<.05) are starred. Overall, 4.8 percent of men were arrested in each year and 1.5 percent were incarcerated. Arrest and incarceration probabilities were about twice as high for black compared to white men. Considering the key variables of interest, approximately one in five men experienced three or more changes in maternal union status. One-sixth of white men and nearly one-third of black men experienced such union instability. In young adulthood, approximately 4 percent of men were married, and 3.6 percent were cohabiting in each year, and 11 percent had become a father. The probability of marriage was lower and the probability of fatherhood higher for black men compared to white men. For both white and black men, approximately 12 percent had a parent who had been arrested or charged with a crime by 1995. Black men had higher caregiver-reported externalizing behavior and more frequent risky behavior (fighting and property damage) in early adulthood compared to white men.

Table 1.

Weighted descriptive characteristics, non-Hispanic white and black men age 18–28, 2005–2015 PSID Transition into Adulthood Supplement

 
 OverallNon-Hispanic
white
Non-Hispanic Black
 MeanSDMeanSDMeanSD
 
Outcomes
 Arrested in year t0.0480.2120.0400.1520.0770.414 *
 In jail in year t0.0150.1210.0130.0870.0240.238 *
Maternal union status change
 0 changes0.5800.4910.6350.3740.3680.750 *
 1 change0.0990.2960.0900.2230.1310.524 *
 2 changes0.1330.3380.1180.2500.1910.611 *
 3+ changes0.1890.3890.1570.2820.3100.719 *
Young adult characteristics
 Non-Hispanic black (vs. NH white)0.2070.4030.000 1.000 
 Married in year t0.0410.1970.0480.1660.0140.186 *
 Cohabiting in year t0.0360.1850.0340.1400.0440.321 *
 Had first child by year t0.1120.3130.0720.2010.2650.686 *
 Age at year t21.1902.39121.1621.86321.2993.775
Family background
Family income-to-needs in 19973.1982.1903.5741.7101.7622.343 *
Mother’s age at birth27.6045.67428.0374.33825.9469.112 *
Mother’s union status at birth
 Married0.7640.4220.8680.2630.3660.749 *
 Never married0.1960.3950.0990.2320.5680.770 *
 Widowed/divorced/separated0.0330.1770.0250.1220.0600.369 *
 Unknown0.0070.0860.0080.0680.0060.124
Mother’s union status in late adolescence
 Partnered with child’s father0.5980.4870.6610.3670.3560.745 *
 Unpartnered0.2440.4270.2010.3110.4080.764 *
 Partnered with other0.1580.3630.1380.2680.2360.660 *
Prior behavior
Either parent ever arrested/charged0.1230.3260.1240.2560.1160.498
Externalizing behavior (0–17, CDS-I or II)5.9373.9645.8123.0286.4166.651 *
Risk-taking in early adulthood ((0–2)0.2060.4410.1780.3080.3160.895 *
Sample information
SRC sample0.8760.3281.0000.0170.4020.762 *
SEO sample0.1240.3280.0000.0170.5980.762 *
Observed to age 16/170.9680.1750.9670.1380.9700.264
 
Number of indviduals1127 586 541 
Number of records6768 3418 3350 

Open in a separate window

*Group differences are statistically significant at p<.05.

Figures 1 to ​to33 provide an assessment of our expectation that men’s contact with the criminal justice system and their own family formation trajectories will differ by maternal union history and race. Figures 1 and ​and22 summarize the incidence of arrest and incarceration at each age by race and by two categories of maternal union status history: having experienced no changes or having experienced three or more changes. At each age, white young adult men who experienced three or more changes in maternal union status were arrested or incarcerated more often compared to same-race peers who experienced no changes in maternal union status. No such disparity appears for black men. Figure 3 describes the proportion of men who were married at each age for the same groups. Marriage rates are low among all men until about age 23. At age 24, those who experienced no maternal union status change pull away from those who experienced 3 changes or more among white men. Among black men, marriage rates remain low, but those who experienced frequent maternal union status change are somewhat more likely to be married compared to their peers who experienced no union status change.

 

 

 

Figure 1.

Incidence of arrest at each age by race and maternal union status history

 

 

 

Figure 2.

Incidence of incarceration at each age by race and maternal union status history

 

 

 

Figure 3.

Proportion of men who were married at each age by race and maternal union status history

Table 2 presents results from multivariate models predicting arrest and incarceration. For each outcome, the baseline model includes indicators of maternal union status change, race, the interaction of race and maternal union status change, and control variables. The full model adds lagged measures of the young adult’s marital status, cohabitation status, and parenthood status at each age. Table 3 reports estimated probabilities from each model, varying exposure to maternal union status change and race and holding all other variables constant at their means.

Table 2.

Coefficients and robust standard errors from logistic regression models estimating log-odds of arrest and jail, non-Hispanic white and black men age 18–28, 2005–2015. PSID Transition to Adulthood Supplement.

 
 ArrestJail
 BaselineFullBaselineFull
 BSEBSEBSEBSE
 
Maternal union status change (vs. none)
 1 change0.2300.3180.3800.3200.2050.5290.4900.534
 2 changes0.2400.3180.3360.3430.0380.5660.4700.589
 3+ changes0.8150.262 **0.8580.290 **0.8630.519 †1.0410.550 †
Non-Hispanic black (vs. NH white)0.5000.261 †0.5480.287 †0.4230.4900.5790.526
 Age at year t0.0070.0210.0100.0290.0250.037−0.0180.050
Union status change * race
1 change * black−0.1020.378−0.3180.391−0.1840.665−0.5780.684
2 changes *black−0.1720.348−0.3160.3670.1770.621−0.3120.642
3 changes * black−0.8910.286 **−0.9020.311 **−0.8570.572−1 .0870.596 †
Family background
Family income-to-needs in 1997−0.1220.037 **−0.0900.040 *−0.2100.079 **−0.1720.088 †
Mother’s age at birth0.0090.0120.0160.0130.0080.0230.0010.023
Mother’s union status at birth (vs. married)
 Never married0.1800.1470.1740.1520.1930.2580.1980.269
 Widowed/divorced/separated0.2380.2430.0800.2570.1790.4220.1890.398
 Unknown−0.2590.536−0.2170.455−0.3761.092−0.2590.949
Mother’s union status in late adolescence
 Unpartnered−0.0480.1650.0130.1780.0390.304−0.1070.336
 Partnered with other−0.2860.201−0.2100.212−0.1010.353−0.4070.362
Prior behavior
Either parent ever arrested/charged−0.0040.1730.0550.180−0.0100.3260.0410.313
Externalizing behavior (0–17, CDS-I or II)−0.0080.013−0.0110.0140.0020.024−0.0130.026
Risk-taking in early adulthood ((0–2)0.5210.099 ***0.4360.107 ***0.5850.177 **0.5790.180 **
Sample information
SEO sample (vs. SRC)0.0680.1960.0240.209−0.0820.314−0.1890.328
Observed to age 16/170.1570.292−0.0430.3340.1260.608−0.1050.606
Own family formation
 Married in year t−1  −2.2351.025 *  −0.4640.758
 Cohabiting in year t−1  0.1870.275  −0.4970.614
 Had first child by year t−1  0.5040.136 ***  0.7890.230 **
 
Intercept−3.5260.677 ***−3.7620.849 ***−4.8781.162 ***−3.6471.411 †
Number of records6768   6754   
 Wald chi−291.720 100.900 59.91 81.210 
 psuedo log-likelihood−1435.920 −1175.880 −598.890 −505.090 

Open in a separate window

**p<.01

*p<.05

†p<.10

Table 3.

Estimated probability of arrest or jail by maternal union status history and race, baseline and full models

 
 ArrestJail
 BaselineFullBaselineFull
 
Non-Hispanic white, no change0.0380.0350.0110.010
Non-Hispanic black, no change0.0610.0590.0170.018
Non-Hispanic white, 1 change0.0470.0500.0140.016
Non-Hispanic black, 1 change0.0690.0620.0180.017
Non-Hispanic white, 2 changes0.0480.0480.0120.016
Non-Hispanic black, 2 changes0.0650.0600.0210.021
Non-Hispanic white, 3 changes0.0820.0780.0270.028
Non-Hispanic black, 3 changes0.0570.0560.0170.017

Open in a separate window

Baseline models indicate that white young adults who experienced three or more maternal union status changes are significantly more likely to be arrested (p<.01) and marginally more likely to be incarcerated (p<.10) in a given year compared to white peers who experienced no maternal union status change net of covariates. Interaction terms indicate that while black men have an elevated likelihood of being arrested or incarcerated compared to white men overall, the probability of these events for black men is unrelated to their history of maternal union status change. This pattern of findings is consistent with prior research on the association of family structure instability with white youths’ behavioral trajectories and with research suggesting that this association is largely absent for black youth.

 

References

  1. Aughinbaugh Alison, Robles Omar and Sun Hugette. 2013. ”Marriage and Divorce: Patterns by Gender, Race, and Educational Attainment.” Monthly Labor Review (October). doi: 10.21916/mlr.2013.32. [CrossRef] [Google Scholar]
  2. Blokland Arjan AJ and Nieuwbeerta Paul. 2005. “The Effects of Life Circumstances on Longitudinal Trajectories of Offending.” Criminology 43(4):1203–40. [Google Scholar]
  3. Bowlby John. 1951. Maternal Care and Mental Health, Vol. 2: World Health Organization; Geneva. [Google Scholar]
  4. Breen Richard, Kristian Bernt Karlson and Anders Holm. 2013. “Total, Direct, and Indirect Effects in Logit and Probit Models.” Sociological Methods & Research 42:164–91. [Google Scholar]
  5. Doherty Elaine Eggleston and Cwick Jaclyn M.. 2016. “Unpacking the Complexity of Life Events and Desistance: An Application of Conjunctive Analysis of Case Configurations to Developmental and Life Course Criminology.” Journal of Developmental and Life-Course Criminology 2(1):45–63. doi: 10.1007/s40865-015-0023-0. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  6. Farrington David P. 2011. “Families and Crime.” Crime and public policy:130–57. [Google Scholar]
  7. Fomby P and Cherlin AJ. 2007. “Family Instability and Child Well-Being.” American Sociological Review 72(2):181–204. [PMC free article] [PubMed] [Google Scholar]
  8. Fomby Paula, Mollborn Stefanie and Christie A Sennott. 2010. “Race/Ethnic Differences in Effects of Family Instability on Adolescents’ Risk Behavior.” Journal of Marriage and Family 72(2):234–53. [PMC free article] [PubMed] [Google Scholar]
  9. Fomby Paula. 2013. “Family Instability and College Enrollment and Completion.” Population Research and Policy Review 32(4):469–94. doi: 10.1007/s11113-013-9284-7. [CrossRef] [Google Scholar]
  10. Fomby Paula and Bosick Stacey J.. 2013. “Family Instability and the Transition to Adulthood.” Journal of Marriage and Family 75(5):1266–87. doi: 10.1111/jomf.12063. [CrossRef] [Google Scholar]
  11. Fomby Paula and Mollborn Stefanie. 2017. “Ecological Instability and Children’s Classroom Behavior in Kindergarten.” Demography 54(5):1627–51. doi: 10.1007/s13524-017-0602-2. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  12. Forrest Walter. 2014. “Cohabitation, Relationship Quality, and Desistance from Crime.” Journal of Marriage and Family 76(3):539–56. [Google Scholar]
  13. Hofferth SL and Goldscheider F. 2010. “Family Structure and the Transition to Early Parenthood.” Demography 47(2):415–37. [PMC free article] [PubMed] [Google Scholar]
  14. Horney Julie, Osgood D. Wayne and Ineke Haen Marshall. 1995. “Criminal Careers in the Short-Term: Intra-Individual Variability in Crime and Its Relation to Local Life Circumstances.” American sociological review 60(5):655–73. [Google Scholar]
  15. Laub John H. and Sampson Robert J.. 2006. Shared Beginnings, Divergent Lives. Cambridge, Massachusetts and London, England: Harvard University Press. [Google Scholar]
  16. Lee D and McLanahan S. 2015. “Family Structure Transitions and Child Development: Instability, Selection, and Population Heterogeneity.” American Sociological Review 80(4):738–63. doi: 10.1177/0003122415592129. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  17. Macmillan Ross and Eliason Scott R.. 2003. “Characterizing the Life Course as Role Configurations and Pathways” Pp. 529–54 in Handbook of the Life Course, edited by Mortimer JT and Shanahan MJ. New York: Kluwer Academic/Plenum Publishers. [Google Scholar]
  18. Macmillan Ross and Hagan John. 2004. “Violence in the Transition to Adulthood: Adolescent Victimization, Education, and Socioeconomic Attainment in Later Life.” Journal of Research on Adolescence 14(2):127–58. [Google Scholar]
  19. Massoglia Michael and Christopher Uggen 2010. “Settling Down and Aging Out: Toward an Interactionist Theory of Desistance and the Transition to Adulthood.” American Journal of Sociology 116(2):543–82. doi: 10.1086/653835. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  20. McGonagle Katherine A., Schoeni Robert F., Sastry Narayan and Freedman Vicki A.. 2012. “The Panel Study of Income Dynamics: Overview, Recent Innovations, and Potential for Life Course Research.” Longitudinal and life course studies 3(2):188. [PMC free article] [PubMed] [Google Scholar]
  21. Osgood, D. Wayne, Gretchen Ruth, Jacquelynne S. Eccles, Janis E. Jacobs and Bonnie L. Barber 2005. “Six Paths to Adulthood: Fast Starters, Parents without Careers, Educated Partners, Educated Singles, Working Singles, and Slow Starters” Pp. 320–55 in On the Frontier of Adulthood, edited by Settersten RA Jr., Furstenberg FF Jr. and Rumbaut RG. Chicago & London: The University of Chicago Press. [Google Scholar]
  22. Peterson James L. and Zill Nicholas. 1986. “Marital Disruption, Parent-Child Relationships, and Behavior Problems in Children.” Journal of Marriage and Family 48:295–307. [Google Scholar]
  23. Raley R. Kelly, Megan M. Sweeney and Danielle Wondra 2015. “The Growing Racial and Ethnic Divide in U.S. Marriage Patterns.” The Future of children / Center for the Future of Children, the David and Lucile Packard Foundation 25(2):89–109. [PMC free article] [PubMed] [Google Scholar]
  24. Rebellon Cesar J. 2002. “Reconsidering the Broken Homes/Delinquency Relationship and Exploring Its Mediating Mechanism (S).” Criminology 40(1):103–36. [Google Scholar]
  25. Sampson Robert J and John H Laub. 1997. “A Life-Course Theory of Cumulative Disadvantage and the Stability of Delinquency.” Developmental theories of crime and delinquency 7:133–61. [Google Scholar]
  26. Sampson Robert J, John H Lauband Christopher Wimer. 2006. “Does Marriage Reduce Crime? A Counterfactual Approach to within‐Individual Causal Effects.” Criminology 44(3):465–508. [Google Scholar]
  27. Sampson Robert J. and Laub John H.. 1995. Crime in the Making: Pathways and Turning Points through Life. Cambridge: Harvard University Press. [Google Scholar]
  28. Census Bureau US. 2017. “Table Ms-2. Estimated Median Age at First Marriage, by Sex: 1890 to the Present.” edited by ms2.xls. Washington, DC: Department of Commerce. [Google Scholar]
  29. Uggen Christopher and Janikula Jennifer. 1999. “Volunteerism and Arrest in the Transition to Adulthood.” Social forces 78(1):331–62. [Google Scholar]
  30. Uggen Christopher. 2000. “Work as a Turning Point in the Life Course of Criminals: A Duration Model of Age, Employment, and Recidivism.” American sociological review 65(4):529–46. [Google Scholar]
  31. Wells L Edwardand Joseph H Rankin. 1991. “Families and Delinquency: A Meta-Analysis of the Impact of Broken Homes.” Social problems 38(1):71–93. [Google Scholar]
  32. Wu LL and Martinson BC. 1993. “Family-Structure and the Risk of a Premarital Birth.” American Sociological Review 58(2):210–32. doi: 10.2307/2095967. [CrossRef] [Google Scholar

 


نویسنده: دکتر حسام رحیمی دسته بندی: کیفری تاریخ ثبت: 00:26 1403/9/11 9 نفر بازدید