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Articles

Unraveling bias in arrest decisions: The role of juvenile offender type-scripts

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Pages 427-457 | Published online: 18 Aug 2006
 

We investigate police decisions to arrest using police contact data from the juvenile offense portion of the 1958 Philadelphia birth cohort. The analysis is based on the assumption that police use type-script (and countertype) heuristics based on suspects' race, gender, socioeconomic status (SES), and offense types to assist in their arrest decisions. We performed logistic regression analyses on police arrest decisions for offenses categorized according to their gender type-script. Like other results, these data show that, in the aggregate and when other variables are controlled, females are less likely to be arrested than their male counterparts and that race and SES also significantly affect the arrest decision. Among all offenses, the gender-typing variable explained a large portion of the effect of gender alone on the arrest decision. Within gender-type offense categories, we found evidence that officers consider offense seriousness and, most notably, the number of prior police contacts in arrest decisions. The latter plays a slightly larger role in the arrest decision for females than for males. Results are confounded by interactions with race and SES.

The authors wish to dedicate this work to Dr. Gary Hill, whose research in this area provided invaluable inspiration. His tremendous support and enthusiasm will always be remembered and appreciated. We also acknowledge the helpful statistical counsel of Denise Gottfredson.

The authors wish to dedicate this work to Dr. Gary Hill, whose research in this area provided invaluable inspiration. His tremendous support and enthusiasm will always be remembered and appreciated. We also acknowledge the helpful statistical counsel of Denise Gottfredson.

Notes

The authors wish to dedicate this work to Dr. Gary Hill, whose research in this area provided invaluable inspiration. His tremendous support and enthusiasm will always be remembered and appreciated. We also acknowledge the helpful statistical counsel of Denise Gottfredson.

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