Incarceration is one of the most extreme exercises of state power. For the past twenty-five years the rates at which states have been locking up their residents have been growing at a distressing pace. While violent crime rates have been declining, arrest rates for lower-level crimes have been steadily rising. Two new indices are developed to explain the relationship between lower-level crime and violent crime--the punitive severity index (PSI) and the punitive progression index (PPI). The PSI is the ratio of low-level crime to violent crime, a static indicator of punitiveness, while the PPI is a measure of the rate of growth towards or away from a more punitive approach to law enforcement. The PSI and probation rates are two important factors for predicting incarceration rates, explaining 98.6% of the variation in incarceration rates.
Hierarchical modeling was used to test hypotheses about the influence of the PSI, the PPI, and other state-level contextual variables on sentence length. At the individual level, the model suggests the race of the inmate has some, though nonsignificant, influence on sentence length. At the state level, PPI is significant (p = .011) for predicting states' average sentence length. Type of state probation system oversight, either judicial or executive, also significantly affected length of sentence, with judicial oversight associated with shorter periods of incarceration.
","abstract_html":"<p>Incarceration is one of the most extreme exercises of state power. For the past twenty-five years the rates at which states have been locking up their residents have been growing at a distressing pace. While violent crime rates have been declining, arrest rates for lower-level crimes have been steadily rising. Two new indices are developed to explain the relationship between lower-level crime and violent crime--the punitive severity index (PSI) and the punitive progression index (PPI). The PSI is the ratio of low-level crime to violent crime, a static indicator of punitiveness, while the PPI is a measure of the rate of growth towards or away from a more punitive approach to law enforcement. The PSI and probation rates are two important factors for predicting incarceration rates, explaining 98.6% of the variation in incarceration rates.</p> <p>Hierarchical modeling was used to test hypotheses about the influence of the PSI, the PPI, and other state-level contextual variables on sentence length. At the individual level, the model suggests the race of the inmate has some, though nonsignificant, influence on sentence length. At the state level, PPI is significant (p = .011) for predicting states' average sentence length. Type of state probation system oversight, either judicial or executive, also significantly affected length of sentence, with judicial oversight associated with shorter periods of incarceration.</p>","abstract_has_math":false,"creators":["Dalton, Teresa A."],"institution":null,"degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":null,"degree_department":null,"school":null,"contributors":["Kathy Green, Ph.D.","Corey Chiochetti","Khawla Obedieta"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2010,"date_issued":"2010-01-01T08:00:00Z","date_published":"2010-01-01T08:00:00Z","updated_at":"2026-07-24T02:02:11Z","subjects":["Criminal justice industrial complex","Hierarchical linear modeling","Punitiveness","Criminal Law","Criminal Procedure","Law"],"languages":["en"],"rights":["Copyright is held by the author. User is responsible for all copyright compliance.
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Hierarchical modeling was used to test hypotheses about the influence of the PSI, the PPI, and other state-level contextual variables on sentence length. At the individual level, the model suggests the race of the inmate has some, though nonsignificant, influence on sentence length. At the state level, PPI is significant (p = .011) for predicting states' average sentence length. Type of state probation system oversight, either judicial or executive, also significantly affected length of sentence, with judicial oversight associated with shorter periods of incarceration.
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Hierarchical modeling was used to test hypotheses about the influence of the PSI, the PPI, and other state-level contextual variables on sentence length. At the individual level, the model suggests the race of the inmate has some, though nonsignificant, influence on sentence length. At the state level, PPI is significant (p = .011) for predicting states' average sentence length. Type of state probation system oversight, either judicial or executive, also significantly affected length of sentence, with judicial oversight associated with shorter periods of incarceration.
"],"dc:format":["application/pdf"],"dc:identifier":["https://digitalcommons.du.edu/etd/795"],"dc:language":["en"],"dc:rights":["Copyright is held by the author. User is responsible for all copyright compliance.
"],"dc:subject":["Criminal justice industrial complex","Hierarchical linear modeling","Punitiveness","Criminal Law","Criminal Procedure","Law"],"dc:title":["The Expanding Definition of Crime and Its Effect on the Individual: A Multilevel Modeling Analysis"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."]},"updated_at":"2026-07-24T02:02:11Z"}