Assessing Gender Differences in Prison Rule Enforcement: A Focus on Defiance

Abstract

This study focuses on gender disparities in defiance prison ­infractions—an understudied and highly discretionary type of rule violation—which have important implications for individuals’ prison experiences and outcomes. Using administrative data on a release population in a large western state (N = 23,818), we employed multilevel modeling techniques to test whether (1) women were more likely than men to receive defiance infractions; (2) whether women received a greater number of defiance infractions than men, and (3) whether the gender differences observed for defiance were unique from other types of infractions (e.g. any infraction, nonviolent, violent) net of individual- and prison unit-level controls. Results confirmed that defiance infractions are uniquely gendered, which subjects incarcerated women to harsh consequences for far less serious behavior than their male counterparts. Our work fills key gaps in the literature and contributes to recent policy reform efforts aimed at prison disciplinary reform.

Keywords:

• Defiance
• gender
• prison
• misconduct

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Notes

1 2,130 individuals (6%) who were admitted to prison before July 1, 2005, were removed from the analysis.

2 To account for potential differences among individuals influenced by the length of time served (e.g., differences in motivation or opportunity to engage in misconduct; (See Cunningham & Sorensen, 2006), and accounting for differences in the risk of receiving infractions among individuals (Orrick & Morris 2015), the study excludes technical violators and individuals who served less than 6 months of a prison term (n = 9,713). A majority of the technical violators served less than 6 months, which reflects the state sentencing policies that individuals only serve the remaining sentence of their original prison term when they are re-incarcerated for the technical violation.

3 Less than one percent of cases in the original data file were coded as “other race” which led us to exclude these cases and retain cases where individuals were categorized as White, Black, Latino/a, and Native American. Five “units” were excluded from the analysis because they were mislabeled in the data and could not be deciphered or they were not actual units (e.g., hospitals, category for those transferred out-of-state as part of interstate compact). These designations included between 16 and 80 individuals, resulting in a total of 239 individuals excluded.

4 The most frequent defiance infractions for women included 1) disorderly conduct, 2) disrupting count or being out of place, and 3) disobeying an order. Over a quarter (29%) of the total infractions in the data among women were concentrated in these three rule violations. What is more, disorderly conduct and disrupting count or being out of place were the two most common infractions among women regardless of infraction type. For men, the most frequent defiance tickets were 1) disrupting count or being out of place, 2) refusal of an assignment, and 3) disorderly conduct. These tickets accounted for approximately 18% of all tickets given to men across infraction categories.

5 It is important to note that drug/alcohol violations were excluded from the nonviolent infraction measure since only three percent of women had a drug or alcohol-related ticket on their record.

6 This state prison system considers individuals’ gender identity preferences and how they believe they would be most safely housed, including placement in male or female housing units. As such, gender classification and where individuals are housed are not restricted to sex assigned at birth.

7 Continuous measures of age and length of time served were centered around the grand mean to correct for skewness in the analysis. This changes the interpretation of these variables to be based on effects that are greater or less than the average.

8 In the state, felonies are categorized into six classes, ranging from 1 to 6. Class 1 felonies are the most serious offenses (e.g., homicide) and Class 6 felonies are the least serious offenses (e.g., possession of drug paraphernalia).

9 Due to the fixed nature of the error variance in logistic regression models, the ICC was calculated using the following formula: ρ= τ00/(τ00+_π2/3) (Raudenbush & Bryk, 2002, p. 334).