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| Criminal Career Paradigm× | Recidivism Survival Analysis× | |
|---|---|---|
| Галузь | Criminology | Criminology |
| Родина≠ | Process / pipeline | Survival analysis |
| Рік появи≠ | 1986 | 1988 |
| Автор методу≠ | Alfred Blumstein, Jacqueline Cohen, Jeffrey Roth & Christy Visher | David R. Cox (method); Peter Schmidt & Ann Dryden Witte (criminological application) |
| Тип≠ | Conceptual framework for decomposing offending over the life course | Time-to-event regression for reoffending |
| Основоположне джерело≠ | Blumstein, A., Cohen, J., Roth, J. A., & Visher, C. A. (Eds.). (1986). Criminal Careers and 'Career Criminals' (Vols. 1–2). National Academy Press. ISBN: 9780309036887 | Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B, 34(2), 187–202. DOI ↗ |
| Інші назви | Criminal Careers Framework, Career Criminal Paradigm, Offending Career Approach, Blumstein Criminal Career Model | Time-to-Recidivism Modeling, Recidivism Hazard Modeling, Failure-Time Analysis of Reoffending, Survival Analysis of Reoffending |
| Пов'язані | 4 | 4 |
| Підсумок≠ | The criminal career paradigm is a framework for studying offending as a longitudinal sequence in an individual's life rather than as undifferentiated aggregate crime. Codified by Blumstein, Cohen, Roth, and Visher in the 1986 National Academy of Sciences report, it decomposes crime into distinct dimensions — whether someone offends (participation), how often active offenders offend (frequency, λ), and the onset, seriousness, and duration of the career — each potentially with different causes. | Recidivism survival analysis models the time from a release or index event until an individual reoffends, treating reoffending as a time-to-event ('failure') outcome with censoring for those not observed to fail. It applies survival methods — Kaplan-Meier curves, Cox proportional-hazards regression, and split-population models — to answer not just whether someone recidivates but how quickly and what raises or lowers that risk over time. |
| ScholarGateНабір даних ↗ |
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