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Objectives: To present and test an opportunity perspective on prison inmate victimization. Methods: Stratified random samples of inmates ( n = 5,640) were selected from Ohio and Kentucky prisons ( n = 46). Bi-level models of the prevalence of assaults and thefts were estimated. Predictors included indicators of inmate routines/guardianship, target antagonism, and target vulnerability at the individual level, and several indicators of guardianship at the facility level. Results: Assaults were more common among inmates with certain routines and characteristics that might have increased their odds of being victimized (e.g., less time spent in recreation; committed violence themselves during incarceration), and higher levels of assaults characterized environments with lower levels of guardianship (e.g., architectural designs with more 'blind spots', larger populations, and less rigorous rule enforcement as perceived by correctional officers). Similar findings emerged for thefts in addition to stronger individual level effects in prisons with weaker guardianship (e.g., ethnic group differences in the risk of theft were greater in facilities with larger populations and less rigorous rule enforcement). Conclusions: The study produced evidence favoring a bi-level opportunity perspective of inmate victimization, with some unique differences in the relevance of particular concepts between prison and non-prison contexts. [ABSTRACT FROM AUTHOR]

A substantial body of empirical research examines how the huge expansion in incarceration in the United States since the early 1970s has influenced crime. These studies merge the effects of three conceptually distinct paths by which incarceration might reduce crime: general deterrence, specific deterrence and incapacitation. This issue of the Journal focuses specifically on the incapacitation path. This Introduction reviews the individual papers and offers the editors’ judgment as to the plausibility of progress using different research strategies. It emphasizes the potential for using individual level data to take advantage of natural experiments. [ABSTRACT FROM AUTHOR]