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Understanding risky facilities: an analysis of factors associated with jail escapes in eight states

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Abstract

There is a dearth of research on the factors that make some jails more prone to escapes than others. Clarke and Eck’s (Understanding risky facilities, US Department of Justice, Office of Community Oriented Policing Services, Washington, DC, 2007) risky facilities framework posits there are seven key factors which predict a facility’s risk to crime and disorder. Using data from 88 county jails in eight contiguous states, this study empirically tests if facility-level risk factors can account for jail escapes. Additionally, this research examines county-level characteristics to account for the macro-level explanations. Jails which had reported an escape during the study year were relatively larger, had higher populations relative to their rated capacities, and employed fewer correctional officers per inmate than their control facilities which did not report an escape. This research discusses policy implications in light of these findings.

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Notes

  1. The small sample size used in this study did not allow for multivariate analyses of all ten independent variables. To run a multivariate analysis, a general rule-of-thumb states a minimum of around 10 cases per variable, with some suggesting even larger sample sizes are needed; for example, Maxwell (2000) argues that the 10:1 ratio is considered extremely small). In this study, we have 10 variables, which would require around 100 cases. As we cannot choose which variables to include or omit, we are currently limited to the univariate and bivariate analyses. Similar univariate analyses have been used in other risky facilities-related publications where small sample sizes existed, such as Petrossian and Clarke (2013) and Pires and Clarke (2012).

  2. Alpha was set at 0.10 in this analysis. This reflects the small sample size and the preliminary nature of the analysis as a pilot study.

  3. Conversely, Peterson (2015) utilized escape rates instead of a dichotomous variable for escapes as the outcome measure for his research and found that rated capacity, another proxy for population size, was inversely related to escapes.

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Authors and Affiliations

  1. John Jay College of Criminal Justice, City University of New York Graduate Center, New York, NY, USA

    Jacqueline Scott, Gohar Petrossian & Jeff Mellow

  2. Urban Institute, Washington, DC, USA

    Bryce Peterson

Authors
  1. Jacqueline Scott
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  2. Gohar Petrossian
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  3. Jeff Mellow
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  4. Bryce Peterson
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Correspondence to Jacqueline Scott.

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Scott, J., Petrossian, G., Mellow, J. et al. Understanding risky facilities: an analysis of factors associated with jail escapes in eight states. Secur J 31, 805–820 (2018). https://doi.org/10.1057/s41284-018-0132-7

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  • DOI: https://doi.org/10.1057/s41284-018-0132-7

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