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The maturing moral perception of crime: The development of moral correspondence and its association with emerging adults’ delinquent involvement

Georg Kessler


Purpose: This study scrutinizes Situational Action Theory’s (SAT) implications of how internal and external criminogenic factors concerning the rule of moral correspondence develop conjointly over the life-course and how this affects offending during emerging adulthood.Objectives: The main objective is to empirically explore whether the development of moral correspondence displays heterogeneity that can be theoretically linked to heterogeneous offending developments. Additionally, the paper also discusses unexpected co-occurrences arising specifically for the new opportunity structures to commit crimes in emerging adulthood via the broader developmental perspective proposed by the Developmental Ecological Action model of SAT (DEA).Methods: Results from two separate classification models (latent class growth analysis and repeated-measurement latent class analysis) following a German non-offender sample’s (N = 1810) transition between adolescence and emerging adulthood (ages 14 to 28) are cross-tabulated.Results: Five moral correspondence pathways differentiated by the timing, speed and completeness of achieving pro-social states can be extracted. The longer individuals resist this maturitation process during adolescence, the higher their chances are to follow a trajectory during emerging adulthood characterized by proclivities for youth crimes. However, these also follow a diminishing trend. Contrary, rising trajectories fueled by proclivities to commit adult crimes are less often associated by a remiss to maturity. Social selection into specific activity fields seems to play an important role in the availability and accessibility to either type of crime, thus, offering an explanation for these diverging results.Conclusion: SAT and its developmental framework DEA serve as useful blueprints to map the development of changes in crime and its related causes even with non-situational data through its analytical rigor to integrate micro-, meso-, and macro-levels of explanation.


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Table A1:
Age of inclusion 1 2 3 4 5 6 7 8
13 – 28 Graffities Scratching Vandalism Machine theft Shoplifting Bicycle theft Motor-vehicletheft Theft out of vehicle
Purse snatching Robbery Burglary Other thefts Accepting-stolen goods Aggrav. assaultw/o a weapon Aggrav. assaultwith a weapon Drug dealing
20 – 28 Driving w/o permit Hit and run Partner violence
22 – 28 Illegal-employment Drunk driving
24 – 28 Ill. advantage-over employer Ill. advantage-for employer
26 – 28 False claims(insurance) False claims(public agency) Tax evasion False represent-tation(sale of goods) Selling goods w/ointent to deliver Fraudul.induce-mentto contract
28 Paying for service w/o bill Illicit upload of proprietary media
Table A2
Model BIC aBIC Entropy LMR p-value
C2 12145.86 12091.86 0.800 0.0000
C3 11969.59 11902.88 0.713 0.0000
C4 11937.06 11857.64 0.703 0.0189
C5 11938.06 11845.92 0.714 0.2805
C6 11923.49 11818.65 0.703 0.7984

Published Online: 2021-10-23
Published in Print: 2021-11-17

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