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Legal Socialization and Self-Reported Criminal Offending: The Role of Procedural Justice and Legal Orientations

Abstract

Objectives

The procedural justice model of legal socialization holds that personal fairness judgments influence criminal offending directly and indirectly, via legal orientations (e.g. legitimacy and legal cynicism). This study used longitudinal data to empirically scrutinize these arguments.

Methods

Using 11 waves of data from the Pathways to Desistance study (i.e. baseline and 10 follow-up interviews), a series of time-lagged, multi-level longitudinal regression models with time-varying and time-stable measures decomposed into between- and within-individual components were estimated.

Results

The estimates from the linear mixed-effects models showed that procedural justice judgments directly influence legitimacy and, though relatively more limited, legal cynicism over time both between- and within-individuals. Test statistics indicated too that positive procedural justice judgments reduce involvement in criminal offending between individuals. However, legitimacy is found to significantly mediate the effect of personal procedural justice judgments. The effect of vicarious procedural justice judgments remained statistically significant in explaining differences in criminal offending. As for the within-individual model, neither procedural justice scale predicted offending. However, legal cynicism did have a direct significant effect in the within-individual offending model.

Conclusions

The findings support key elements legal socialization theory, especially the premise that the way in which criminal justice authorities treat the individuals they come into contact with influences (albeit indirectly) subsequent compliance with the law.

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Notes

  1. The objective here is to provide readers with an idea of the relative strength of the hypothesized relationships in different studies. While some readers might prefer standardized partial regression coefficients, different reporting practices from one study to the next did not allow for the reporting such estimates. Accordingly, bivariate estimates are used because they were widely available and, though less robust than standardized regression estimate, because they allow readers to make judgments regarding the relative strength of relationships.

  2. A small but growing body of legal socialization research has employed samples of criminal justice involved individuals, including people who are incarcerated (Reisig and Meško 2009; Baker et al. 2014), individuals with recent contact with the police or courts (Tyler and Huo 2002), and court defendants (Baker 2017).

  3. For more information on the procedural justice measures can be found at www.pathwaysstudy.pitt.edu/codebook/procedural-justice-sf.html. The full list of procedural justice items can be found in Augustyn (2016, pp. 277–279) and an exhaustive list of items can be found in Piquero et al. (2005, p. 278).

  4. Although confirmatory factor modeling would help determine whether combining police and court judgments into personal and vicarious procedural justice measures is empirically justified, the available Pathways data do not provide the individual survey items necessary to estimate such models. There is reason to conclude that the constructs are valid. First, prior work has demonstrated the consistent trajectories for personal procedural justice of both police and courts over time using the Pathways data (which differ from the trajectories of vicarious procedural justice; see Kaiser 2016). Further, when assessing the correlations for the procedural justice measures—personal/police, personal/courts, vicarious/police, and vicarious/courts—the two personal measures are more strongly correlated relative to the correlations for mixed sources (e.g. personal/police and vicarious police). This pattern held when evaluating the vicarious measures. Finally, the distinction between personal and vicarious (also known as general and specific) procedural justice is consistent with prior research (see Gau 2014; Murphy et al. 2014).

  5. Unconditional growth curve models were used to assess the magnitude of the variation within individuals for the variables of theoretical interest. According to the within-individual (level 1) error terms in the models, there is statistically significant within-individual variation across time for all for variables: personal procedural justice (b = .507, SE = .004, p < .001) vicarious procedural justice (b = .468, SE = .046, p < .001), legitimacy (b = .387, SE = .003, p < .001), and legal cynicism (b = .433, SE = .003, p < .001).

  6. To ensure the robustness of observed findings, separate analyses were conducted whereby personal and vicarious procedural justice judgments of police and courts were disaggregated. Specifically, models were estimated with separate measures for personal and vicarious procedural justice of police and separate measures for vicarious and personal procedural justice of courts. The procedural justice measures in these subsequent analyses performed as follows: between-individual differences of police procedural justice (b = − .192, SE = .052, p < .001, for personal and b = − .183, SE = .047, p < .001, for vicarious); within-individual change in police procedural justice (b = .032, SE = .022, for personal and b = .021, SE = .027, for vicarious); between-individual differences in courts procedural justice (b = − .063, SE = .054, for personal and b = − .106, SE = .046, p < .01, for vicarious); and, within-individual change in courts procedural justice (b = − .063, SE = .054, for personal and b = − .012, SE = .026, for vicarious). Though some modest differences between the police and courts measures were observed, the results are very similar in terms of sign and significance level.

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Acknowledgements

The authors wish to thank for Gary Sweeten for his statistical advice and helpful comments.

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Correspondence to Kimberly Kaiser.

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Kaiser, K., Reisig, M.D. Legal Socialization and Self-Reported Criminal Offending: The Role of Procedural Justice and Legal Orientations. J Quant Criminol 35, 135–154 (2019). https://doi.org/10.1007/s10940-017-9375-4

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  • DOI: https://doi.org/10.1007/s10940-017-9375-4

Keywords

  • Life course
  • Desistance
  • Recidivism
  • Process-based model
  • Longitudinal analysis