Incarceration rates rose to unprecedented levels in the history of the U.S.’s imprisonment. Therefore, concern about social control of the incarcerated, that is, prisoners’ behavior, has increased. High inmate disciplinary infractions, especially violent infractions, are a threat to the safety of prison, of correctional staff, and of other inmates. Nevertheless, the issue of discipline in prison is important from an economic perspective, because an estimated average cost per infraction at a medium security prison is $970 (Jiang & Fisher-Giorlando, 2002). For these reasons, Jiang & Fisher- Giorlando conducted a research to help explain violent incidents, incidents against correctional staff and incidents against other inmates in prison. Identifying the risk factors of inmates to commit violent acts of misconduct is of great importance to prison administration. This type of research can assist in the classification process of inmates entering institutions as well as the ongoing classification adjustments of inmates already in custody.
This study will identify and investigate factors for violent institutional misconduct. These factors include; however, are not limited to race, age, education and employment, family ties, length of sentence, security level, prison environment and gender. The hypotheses of this study are:
1. Violent prison misconduct is more prevalent among African-American and Hispanic inmates than Caucasians or any other ethnic group. 2. Inmates who are residing in maximum-security facilities are more violent than inmates residing in medium or minimum-security facilities, especially towards correctional staff.
Several studies were conducted to examine the role of race in inmate adjustment process and prison misconduct, especially prison violence. There were indications that there is a direct relationship between race and violent prison misconduct. Those findings support theories such as prison adjustment and subculture of violence, which say that minority groups have
higher rates of violence in prison society than white inmates (DeLisi et al., 2004; Griffin & Hepburn, 2006; Gillespie, W., 2005; Jiang & Fisher-Giorlando, 2002; Steiner & Wooldredge, 2009). According to Wayne Gillespie (2005), Caucasian inmates appear less likely to engage in most types of misconduct compared to African American and Hispanic inmates. Blacks are more likely than Whites to evoke protective violent responses to perceived dangerous situations or threats of physical injury by aggressive, violent behavior aimed at protecting self or preventing retaliation (Gillespie, W., 2005).
Age and prison violence had an inverse relationship. The older inmates were, the less likely they were to be involved in violent prison misconduct. Younger inmates were significantly more likely to be involved in violent prison misconduct. This relationship was widespread throughout all the studies (Cunningham & Sorensen, 2007; DeLisi et al., 2004; Griffin & Hepburn, 2006; Jiang & Fisher-Giorlando, 2005; Ruddell et al., 2006; Sorensen & Cunningham, 2008).
Education and Employment
Research shows an inverse relationship between level of education and rates of prison misconduct. As level of education increased, involvement in violent prison misconduct decreased (Cunningham & Sorensen, 2007; DeLisi et al., 2004; Wooldredge et al., 2001). As stated by Wooldredge, Griffin, and Pratt (2001), inmates who were employed prior to incarceration were less likely to be involved in violent prison misconduct. This group was more invested in conforming because they had more to lose. Inmates who worked prior incarceration were more likely than other inmates to be concerned with going home and continuing employment.
Social and family support was inversely related to violent prison misconduct
(Cunningham & Sorensen, 2007; DeLisi et al., 2004; Jiang & Fisher-Giorlando, 2005; Wooldredge et al., 2001). Inmates with less social and familial support committed significantly more acts of serious prison violence (DeLisi et al., 2004). Moreover, inmates who made and received more telephone calls from children were less likely to commit violent rule violations (Jiang, Fisher-Giorlando & Mo, 2005).
According to Jiang and colleagues (2005) inmates with strong family ties had more to lose if they were involved in violent prison misconduct. Sources of family support included mail, telephone calls, and visitations. Rule violations could result in loss of visiting privileges, which is a strong source of strengthening family ties.
Length of Sentence
The relationship between length of current sentence that inmates are serving and violent prison misconduct is debatable. Inmates with shorter sentences were more likely to commit violent acts. Short term sentenced inmates were usually younger and they still possessed a street mentality. Inmates with longer sentences were usually older and appeared to better understand the need to co-exist with other inmates as well as correctional staff (Wooldredge et al., 2001).
Several studies showed that security level is a predictor of rule violation (Camp et al., 2003; Jiang & Fisher-Giorlando, 2002; Steiner & Wooldredge, 2008). To be more specific, inmates residing in working cell-blocks and dormitories are less likely than are those in lock-down cell-blocks to commit violence and incidents against correctional staff (Jiang & Fisher-Giorlando, 2002). Prison Environment
Prison environment exerts an influence on inmate misconduct, especially interpersonal violence (Blackburn et al., 2007; Camp et al., 2003; Steiner & Wooldredge, 2008). Research conducted by Camp et al., (2003) indicated that
prison’s organizational factors influenced inmates’ behavior that led to violent misconduct. Furthermore, institutions with inexperienced staff had greater report numbers of inmate misconduct. Moreover, prison crowding, as one of the ecological factors, influenced inmate behavior because it produces intermediate psychological states, such as depression that then lead to misconduct (Camp et al., 2003). Gender
Previous studies showed that gender was inversely related to violent prison misconduct (Blackburn et al., 2007; Camp et al., 2003; Wolff et al., 2009). Male inmates reported higher percentage of physical victimization perpetrated by staff, although percentage of inmate on inmate physical victimization was equal for male and female inmates (Wolff et al., 2009). This suggests gender-patterned interactions between inmate and staff in which male inmates compared to female inmates are more aggressive against authority figures. In summary, what is known from the literature reviewed is that some factors might influence inmates’ behavior. What is missing is the correlation between those factors and prison violent misconduct, which is addressed by my study. Key variables identified in the reviewed literature are race, age, education and employment, family ties, length of sentence, security level and prison environment, which are incorporated into the study’s methodology as survey and focus group questions. Theoretical Review
To explain inmate behavior in prison three major theoretical models have been proposed. They are the deprivation, importation, and situational models. A true explanation of violent inmate misconduct lies in a combination of those three theories. However, the importation model can be use as the most legitimate singular explanation of violent prison misconduct. The main focus of an importation model is on the influence of pre- prison socialization and experience of the inmate on his/her behavior while being incarcerated (Jiang & Fisher- Giorlando, 2002). According to Jiang & Fisher- Giorlando (2002) inmates’ behavior can be largely determine by their distinctive traits and social backgrounds. The importation model is a reflection of a pre- prison norms and beliefs system of an inmate rather than a result of incarceration in a facility (Irvin &
Cressey, 1962; as cited in Jiang & Fisher-Giorlando, 2002). As importation model implies inmate behavior while being behind the bars is an extension of the antisocial behaviors that criminal offenders developed in the community (DeLisi et al., 2004).
The research design that I used was the analysis of an existing database. I downloaded and analyzed an existing data source from the National Archives of Criminal Justice Data, which can be found at www.ICPSR.org. The data source that I downloaded and analyzed has number 24642 and the title of it is Census of State and Federal Adult Correctional Facilities. The principle investigator of this study is United States Department of Justice, Bureau of Justice Statistics, and the time period is January 1st, 2005 to December 30th, 2005. I chose this dataset because it contains the information needed to do my study on prison violence misconduct.
The 2005 Census of State and Federal Adult Correctional Facilities is the seventh enumeration of State institutions and the fourth of Federal institutions sponsored by the Bureau of Justice Statistics and its predecessors. Earlier censuses were completed in 1974, 1979, 1984, 1990, 1995 and 2000. The facility universe was developed from the Census of State and Federal Adult Correctional Facilities conducted in 2000. In 2000, data were collected from 84 federal facilities and 1,584 non-federal facilities operating on June 30th, 2000. In 2005, each State’s Department of Corrections was contacted to identify new facilities and facilities that had been closed since June 2000. Telephone follow-ups were carried out during 2006. All but one respondent-State of Illinois- participated in the Census.My study determines if in a time period between January 1st, 2005 and December 30th, 2005, the correctional facilities used in existing dataset 24642 experienced physical or sexual assaults, misconduct against correctional staff and misconduct against other inmates. The response options for dependent variables have values such as: 1 which is label Yes, 2 which is label No, and 9 or 999 which is label Missing.
This study aims to determine if independent variables such as race, age, education and employment, family ties, length of sentence, security level, prison environment and gender have a strong correlation with the dependent variables. Data Analysis
For my analyses, I used SPSS Statistics program in version 18.0. I ran frequencies and descriptive tests on both dependent and independent variables. Moreover, I ran ANOVA and t-test to test how facility security levels and race/ethnicity of the inmates impact or don’t the amount of violence.
Table 1: Age of the inmates residing in the facilities during the 1- year period of 2005 (Independent Variable).
|Descriptive Statistics | | | | |Frequency |Percent |Valid Percent |Cumulative Percent | |Valid |Yes |475 |26.1 |28.6 |
As seen in Table 2, during the 1-year period of 2005, 28.6 percent of facilities indicated that yes, there were physical or sexual assaults. The other 71.4 percent indicated that there were no physical or sexual assaults. As seen below in Table 3, during the same year period there was an average of just under 16 inmate-on-inmate assaults at facilities. I also ran a frequency table of staff deaths by inmates, but there were very few.
Table 3: During the 1- year period of 2005 how many inmate on inmates assaults
| | | | | |N |Minimum |Maximum |Mean | |
| | | | | |Y1_BETWEEN 1/1/2005 AND 12/30/2005 WERE THERE PHYSICAL OR SEXUAL ASSAULTS |
The results in the above tables test my hypothesis about how facility security levels impact (or don’t) the amount of violence, using three different measures of the dependent variable: physical or sexual assaults; inmate deaths; and inmate-on-inmate assaults. I ran three ANOVA (analysis of variance) tests, and the results are shown above. Only the ANOVA tests for Y1 and Y3 were statistically significant. There was no difference by security level in the number of staff deaths by inmates, probably because those were low to begin with. However, in terms of physical and sexual assaults (Y1), these were highest at minimum and low-security facilities (mean =1.91). In terms of inmate-on-inmate assaults, these were highest Maximum/close/high facilities, with an average of nearly 34 assaults by inmates on other inmates in 2005. Table 7: Type of Violence by Race/Ethnicity
| | |Y1_BETWEEN 1/1/2005 |Y3_BETWEEN 1/1/2005 | | | |AND 12/30/2005 WERE |AND 12/30/2005 HOW | | | |THERE PHYSICAL OR |MANY INMATE ON | | | |SEXUAL ASSAULTS |INMATES ASSAULTS | |X1_race_white |Pearson Correlation |-.391(**) |.341(**) | | |Sig. (2-tailed) |.000 |.000 | | |N |1631 |1665 | |X1_race_black |Pearson Correlation |-.453(**) |.392(**) | | |Sig. (2-tailed) |.000 |.000 | | |N |1625 |1657 | |X1_race_ethnicity_Hispanic |Pearson Correlation |-.290(**) |.202(**) | | |Sig. (2-tailed) |.000 |.000 | |
|N |1450 |1479 |
** Correlation is significant at the 0.01 level (2-tailed).
As seen above in Table 7, both White and Black race, as well as Hispanic ethnicity, were statistically significantly related to dependent variables Y1 and Y3. Y2 is not shown in the table format because neither race nor ethnicity was related to staff deaths by inmates. Again, this may be due to the small number of staff deaths. An odd pattern emerges: Y1 (number of physical and sexual assaults) was significantly and negatively related to all three race/ethnicity variables. On the other hand, Y3 (number of inmate-on-inmate assaults) was positively and significantly related to all three race/ethnicity variables. The reasons for this are not clear, but may have something to do with the meaning of the questions asked for Y1 and Y3. As for the size of the correlation coefficient, it is the highest for Blacks (r= -.453 and .392), next highest for Whites (r= -.391 and .341), and lowest for Hispanics (r= -.29 and .202).
To return to my first original hypothesis that violent prison misconduct is more prevalent among African-American and Hispanic inmates than Caucasians or any other ethnic group
I have to say that my findings only partially support that statement. According to my results violence among or by African- American inmates appears to be the highest, and is followed by violence among or by White inmates. However, violence by or among Hispanic inmates is the lowest comparing it to violence among or by other races. Moreover, my findings on the impact of security level of facility on prison violence were not exactly what I expected because they differ depending on a type of an assault. Therefore, they partially support my second hypothesis that inmates who are residing in maximum-security facilities are more violent than inmates residing in medium or minimum-security facilities, especially towards
correctional staff. I found that counter to what I expected, super-maximum facilities are not the most dangerous correctional institutions but they have the highest inmate on inmate number of assaults.
Findings from this study about how race impact prison violence partially support what I have found previously in the literature review. According to Wayne Gillespie (2005) and my findings White inmates less likely engage in most types of misconduct compared to African-American inmates but not Hispanic inmates. However, my results on the impact of security level of facility and prison violence are interesting because they do support the findings mentioned in the literature review. All the findings suggest that security level does affect the amount of in-facility violence, but that differs by the type of violence.
Limitation of the Study
While conducting my research by using existing database I had to face a few problems with it. First of all, the database I found had a lot of variables, which had a value that was missing. Second of all, when I ran the tests such as descriptive or frequencies it was hard to describe the results because they were confusing. I wasn’t sure in some cases if the results showed me the number of inmates or the number of facilities. I tried to go back and find the answers in the codebook, which didn’t really contain much more information than the database. Moreover, the meaning of the questions that were asked, especially for dependent variables, wasn’t clear and I believe it impacted somehow the results of the tests I ran.
Blackburn, A. G., Mullings, J. L., Marquart, J. W., & Trulson, C. R. (2007). The next generation of prisoners: Toward an understanding of violent institutionalized delinquents. Youth Violence and Juvenile Justice, 5(1), 35-56. Document ID: 1541204006295156. Camp, S. D., Gaes, G. G., Langan, N. P., & Saylor, W. G. (2003). The influence of prisons on inmate misconduct: A multilevel investigation. Justice Quarterly, JQ, 20(3), 501-533. Document ID: 434413761. Cunningham, M. D., & Sorensen, J. R. (2007). Predictive
factors for violent misconduct in close custody. The Prison Journal, 87(2), 241-253. Document ID: 0032885507303752. DeLisi, M., Berg, M. T., & Hochstetler, A. (2004). Gang members, career criminals and prison violence: Further specification of the importation model of inmate behavior. Criminal Justice Studies, 17(4), 369-383. Document ID: 10.1080/1478601042000314883. Gillespie Wayne, (2005). Racial differences in violence and self-esteem among prison inmates. American Journal of Criminal Justice: AJCJ, 29(2), 161-V. Document ID: 972985931. Griffin, M. L., & Hepburn, J. R. (2006). The effects of gang affiliation on violent misconduct among inmates during the early years of confinement. Criminal Justice and Behavior, 33(4), 419-448. Document ID: 0093854806288038.
Irvin, J., & Cressey, D. (1962). Thieves, convicts, and the inmate culture. Social Problems, 10, 142-155.
Jiang, S., & Fisher-Giorlando, M. (2002). Inmate misconduct: A test of the deprivation, importation, and situational models. The Prison Journal, 82(3), 335-358. Document ID: 003288550208200303. Jiang, S., Fisher-Giorlando, M., & Mo, L. (2005). Social support and inmate rule violation: A multilevel analysis. American Journal of Criminal Justice, 30(1), 71-89. Retrieved from http://proquest.umi.com Ruddell, R., Decker, S. H., & Egley Jr., A. (2006). Gang intervention in jails: A national analysis. Criminal Justice Review, 31(1), 33-46. Document ID: 0734016806288263. Sorensen, J., & Cunningham, M.D. (2008). Conviction offense and prison violence: A comparative study of murderers and other offenders. Crime and Delinquency, 56(1), 103-125. Document ID: 0011128707307175. Steiner, B., & Wooldredge, J. (2008). Inmate versus environmental effects on prison rule violations. Criminal Justice and Behavioral, 35(4), 438. Document ID: 1455568521. Wolff, N., Shi, J., & Siegel, J. (2009). Patterns of victimization among male and female inmates: Evidence of an Enduring Legacy. Violence and Victims, 24(4), 469-84. Document ID: 1825737261. Wooldredge, J., Griffin, T., & Pratt, T. (2001). Considering hierarchical models for research on inmate behavior: Predicting misconduct with multilevel data. Justice Quarterly, 18(1), 203-231. Retrieved from http:// proquest.umi.com