title: Criminal careers behind bars.
abstract: In the criminal career literature, prison is usually viewed as an interruption of offending. Little research has applied the criminal career perspective to misconduct committed by prisoners. The current study used official data from a probability sample of 1,005 inmates from the southwestern United States to examine offending careers during incarceration. Descriptive and negative binomial regression analyses produced findings that suggest both similarities and dissimilarities between conventional and prison criminal careers. The incidence and prevalence of crime were inversely related to its seriousness but the magnitude of crime was higher in prison. One-third of inmates were never contacted for a prison violation and 74% were never contacted for a serious/violent violation. On the other hand, 40% of inmates were chronic or extreme career offenders even while incarcerated. A small cadre of inmates accounted for 100% of the murders, 75% of the rapes, 80% of the arsons, and 50% of the aggravated assaults occurring behind bars. Finally, prior criminality was the best predictor of prison offending, which is supportive of the importation model. While a significant number of inmates fully comply with prison rules, an even larger percentage of inmates continue to commit an array of crimes and rule violations despite the efforts of prison officials.
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D002321:Career Choice; D003415:Crime / Q000145:classification / Q000523:psychology / Q000706:statistics & numerical data*; D003417:Criminal Psychology / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D015994:Incidence; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011329:Prisoners / Q000523:psychology* / Q000706:statistics & numerical data*; D011330:Prisons; D012044:Regression Analysis; D012106:Research; D015206:Southwestern United States / Q000453:epidemiology; D014754:Violence / Q000145:classification / Q000523:psychology / Q000706:statistics & numerical data*