Mass Incarceration Through a Different Lens: Race, Subcontext, and Perceptions of Punitiveness of Correctional Alternatives When Compared to Prison

Abstract

In spite of documented harmful effects of mass incarceration, evidence to date suggests that Blacks perceive the experience of prison as less punitive than Whites. While these findings are well documented, little is known about the role of sociodemographic or contextual factors in shaping this pattern. Utilizing a quantitative intersectional framework, we analyze data from over 1000 Kentucky prison inmates who were within 12 months of their parole hearing or release date to examine the differential effects of various sociodemographic and contextual factors on perceptions of the punitiveness of regular probation, community service, and electronic monitoring (as opposed to prison) for Blacks and Whites. Findings confirm the presence of a racial gap in perceptions of the punitiveness of various alternatives to incarceration; however, results from models disaggregated by race highlight important differences in the effects of gender, parenting, and childhood locale on these perceptions. These findings demonstrate the role of various factors in shaping Blacks’ and Whites’ differential perceptions and reveal the contexts where these differences are most likely to be found.

Introduction

Mass incarceration in the United States has had a particularly detrimental impact on the African American community, and this situation is not new. Tonry (1996) observes that Black Americans have been incarcerated at higher rates than White Americans for over 100 years. The disparity between White and Black incarceration rates increased dramatically in the 1980s and 1990s and continues to grow. Tonry (2011) notes that, since the mid-1980s, incarceration rates for African Americans have been between 5 and 7 times higher than those rates for Whites. On December 31, 2011, the rate of incarceration in prison for Black men (3,023 per 100,000) was 6 times higher than the rate of incarceration in prison (478 per 100,000) for White males, and the rate of Black females incarcerated in prison (129 per 100,000) was approximately 2.5 times higher than that of White females (51 per 100,000; Carson & Sabol, 2012).

A number of scholars have identified ways in which mass incarceration has collateral consequences for both individuals (Manza & Uggen, 2006; Mauer & Chesney-Lind, 2002) and for communities where incarceration rates are particularly high (Clear, 2007). Most authors who examine the impact of mass incarceration note that mass incarceration has had a particularly harmful impact on the African American community (Alexander, 2010; Tonry, 2011; Western, 2006). Despite this fact, Blacks’ perceptions regarding the punitiveness of prison may be surprising to those unfamiliar with that literature. One of the most accepted findings in the area of perceptions of the punitiveness of prison is that Black individuals find prison less punitive, and community sanctions more onerous, than their White counterparts (Applegate, 2014; May, Minor, Wood, & Mooney, 2004; May & Wood, 2005, 2010; May, Wood, Mooney, & Minor, 2005; Petersilia & Deschenes, 1994a; Spelman, 1995; Williams, May, & Wood, 2008; Wood & Grasmick, 1999; Wood & May, 2003; Wood, May, & Grasmick, 2005).

Despite evidence demonstrating the impact of race on perceptions of punitiveness, a number of questions remain. For example, does the impact of gender or other demographic characteristics on perceptions of punitiveness vary by race? Additionally, are there contextual factors that explain perceptions of punitiveness by race? In this article, we utilize an intersectional framework, based in feminist scholarship (e.g., Crenshaw, 1989; McCall, 2005), to examine subcontexts that may be important for moderating the relationship between race and perceived punitiveness. We determine that the impact of race on perceived punitiveness of prison is significant, and the factors that impact this relationship vary by the type of punishment being considered. We conclude by offering explanations for these findings and suggestions for future research

Literature Review

Previous studies have examined differences in inmate perceptions of alternative sanctions ssin comparison to a prison sentence (see Applegate, 2014; May & Wood, 2010, for review). Punishments used in lieu of prison sentences are attractive for a variety of reasons. First, alternative sanctions are less expensive than incarceration, and expanding the use of alternative sanctions would reduce the costs associated with traditional incarceration. Second, alternative sanctions can reduce prison over- crowding by placing convicted offenders under supervision in the community rather than in prison. Third, when the level of risk that offenders pose is too high for regular probation but not high enough for prison, alternative sanctions can be a viable solution. Fourth, alternatives may provide a better chance for rehabilitation and reintegration because they avoid the negative impacts of prison and maintain positive contacts with family and community. Finally, gauging the punitiveness of alternative sanctions as opposed to prison helps detail the continuum of sentencing options by developing punishment “equivalencies” between noncustodial and custodial sanctions (Byrne, Lurigio, & Petersilia, 1992; May & Wood, 2010; Morris & Tonry, 1990; National Institute of Justice, 1995; Petersilia, 1990).

May and Wood (2010) and Von Hirsch, Wasik, and Greene (1992, p. 377) have argued for the development of a “theory of sentence severity.” They suggest that development of this theory is important both to understand what is meant by sentence severity and to identify factors that influence how sanctions are experienced and ranked by groups affected by correctional sentences (e.g., inmates, offenders supervised in the community, and corrections professionals). A number of studies (see May & Wood, 2010, for review) have used survey methods to measure the perceived severity of correctional sanctions, but, as Von Hirsch et al. note, these studies do not address what is meant by severity, nor do they spend much time in understanding respondents’ reasons for their rankings.

Despite the valid criticism of the lack of theory in this area, evidence has accumulated to the point where scholars now recognize that offenders’ perceptions of punitiveness or severity of criminal sanctions are more complex than previously assumed (e.g., May & Wood, 2010; McClelland & Alpert, 1985; Petersilia, 1990; Spelman, 1995; Wood & Grasmick, 1999; Wood & May, 2003). Early work by the Rand Corporation (Petersilia, 1990) found that, given the choice, up to a third of offenders preferred a prison term over intensive probation supervision in the community. Since that work, researchers have examined patterns of group variation in perceptions of punitiveness among diverse samples. Variation in these perceptions exists along both demographic and experiential lines (Apospori & Alpert, 1993; Crouch, 1993; May et al., 2005; Petersilia & Deschenes, 1994a, 1994b; Spelman, 1995; Wood & Grasmick, 1999; Wood & May, 2003) and appears to be consistent regardless of whether an individual is serving a community-based sanction (Flory, May, Minor, & Wood, 2006; Spelman, 1995; Wood & May, 2003), jail (Applegate, 2014), or prison (Crouch, 1993; May & Wood, 2010; Petersilia & Deschenes, 1994a, 1994b; Wood & Grasmick, 1999). One of the clearest differences in perceptions of punitiveness emerges in the area of race.

Exchange Rates

Attempts to measure offenders’ perceptions of alternative sanctions in comparison to prison have employed a method called the “exchange rate.” May, Wood, Mooney, and Minor (2005) have used this method to rank perceived punitiveness of various correctional alternatives when compared to prison. To calculate an exchange rate, the respondent is given a description of a variety of correctional sanctions and is asked to indicate how many months of each sanction they would be willing to serve to avoid 12 months in a medium-security correctional facility. Through this method, May and Wood (2010) developed “exchange rates” that allow them to compare perceptions of the punitiveness of noncustodial sanctions compared to prison among a wide variety of offender groups (including prisoners, probationers, and parolees), probation/parole officers, judges, and the general public.

Research using “exchange rates” has consistently found that Blacks view prison as less punitive than Whites (see May & Wood, 2010, for review). After exploring a variety of possible explanations for these racial differences, Applegate (2014) reviewed eight proposed explanations for why Black offenders might find prison less onerous than Whites. These eight explanations include that Blacks are more likely than Whites to: (1) consider alternative sanctions as a gamble because they fear they will be revoked, (2) view alternative sanctions and their conditions as a hassle, (3) have higher numbers of relatives, friends, or family who have been incarcerated, (4) have higher levels of respect for individuals who have been to prison, (5) live in neighborhoods with poorer living conditions, (6) feel that community correction programs offer little help in rehabilitation, (7) have weaker community ties, and (8) have previous correctional experience. Applegate (2014) analyzed data from 393 inmates in a Florida jail to determine how the effect of race on perceived sanction severity was mediated by these factors. He found that White respondents were willing to serve an average of 6 months longer on regular probation than Black respondents to avoid a year in prison. However, of the eight explanations noted above, only two were significantly related to the “exchange rate.” Applegate determined that inmates who (a) had neighbors they believed had been incarcerated and (b) felt community correction sentences were a hassle were significantly more likely to rate prison as less punitive than alternative sanctions. Nevertheless, the impact of race on perceptions of punitiveness remained statistically significant, even after including measures representing all eight possible explanations. Applegate concluded that these explanations could not fully explain the racial gap between Blacks and White perceptions of punitiveness and encouraged future research to consider other potential explanations for the observed race difference.

This research is an answer to that call. We focus on racial differences in the perceived punitiveness of three alternatives compared to incarceration: regular probation, community service, and electronic monitoring. In addition to considering the extent of the Black–White gap, we also examine whether these racial differences are influenced by social background and family incarceration history and whether the influences of these subcontexts vary by race.

Methods

Data

Data for this study were collected during the fall of 2010 in cooperation with the Kentucky Department of Corrections. Six prisons were selected based on their ability to yield large enough proportions of Black and female inmates to make meaningful comparisons. In order to collect data from inmates who were seriously considering life outside of prison upon release, researchers identified inmates who were within 12 months of their parole hearing or release date for possible inclusion.

Inmates completed a 15-page self-administered questionnaire adapted from a questionnaire used by Wood, May, and Grasmick (2005) in previous research (see May & Wood, 2010, for a review of those studies).1 Respondents were presented with a range of questions designed to assess demographic characteristics as well as their personal correctional experiences and histories, along with a number of questions regarding the causes and consequences of their criminal involvement, their experiences with correctional programming, their perceptions of the likelihood of recidivism, and their perceptions of the punitiveness of correctional alternatives when compared to incarceration. A total of 1,234 inmates participated in the study, representing approximately 11% of inmates housed in minimum- and medium-security facilities operated by the State of Kentucky in July 2010.2 Listwise deletion of cases resulted in a final sample size of 1,024.3

Measures

The survey presented respondents with a number of correctional alternatives to which people may be sentenced instead of prison. After reading the description of each alternative, respondents were asked to provide the number of months they would take to avoid serving 12 months of actual time in prison. In this study, we focus on respondents’ perceptions of three correctional alternatives: regular probation, community service, and electronic monitoring (see Table 1 for questionnaire descriptions).

Table 1.

Description of Correctional Alternatives Used in Study.

Correctional Alternative	Questionnaire Description
Regular probation	On probation, you do not spend time in prison, but the amount of time on probation usually lasts much longer than whatever prison sentence you might have gotten. You must see your probation officer at least once a month, but it can be every week if ordered. You must get permission from that probation officer to travel or to move. Your probation officer can require that you stay away from certain people. Your home or car can be searched at any time without a search warrant. If you do not follow the rules you can be sent to prison. You are also subject to random urinalysis tests
Community service	When you are sentenced to community service, you live at home and can have a job. However, you must work some time without pay to make up for the crime for which you were convicted. You work for a government agency or some local nonprofit organization, and you do not have any choice about where or what the job is. The judge decides the number of days and hours you must work. If you fail to work the required days and hours, you can be sent back to prison. You are also subject to random urinalysis testing.
Electronic monitoring	On electronic monitoring, you live at home, but your freedom is greatly reduced. You wear an electronic device on your ankle. If you get more than 200 feet from your telephone, the device sends an alarm to a computer. Then, an officer who is supervising you knows that you are not where you are supposed to be. On electronic monitoring you are being followed by the computer 24 hours a day. There are strict curfews and rules about when you must stay near your phone. If you break these rules, you can be sent to prison. You are subject to random urinalysis tests and can be sent back to prison if you fail to obey the rules.

These three alternatives are similar in that they each offer the opportunity to live at home and be employed while serving a sentence. In addition, all three descriptions note that failure to follow the rules can result in being revoked to prison. These alternatives differ in the nature and degree of oversight and the type of reporting required. Both regular probation and electronic monitoring place restrictions on individual movement. With regular probation, however, the level of oversight is decided by a single probation officer and can vary dramatically, whereas with electronic monitoring, officers electronically monitor movement based on a restrictive but stable set of rules. In contrast, community service does not require the same level of oversight or restrictions on physical movement; it does, however, require that individuals work without pay. Although the kind of work individuals are assigned to may vary, many of their assigned tasks may be janitorial or street- cleaning jobs where workers wear brightly colored vests, possibly making their sentence a public spectacle.

In this study, we argue that an inmate has a preference for an alternative sanction over prison when that inmate rates an alternative to incarceration as less punitive than incarceration in prison. As the literature reviewed above suggests, it is well established that males, Blacks, and those who have been incarcerated are willing to serve fewer months on alternative sanctions to avoid incarceration in prison than their counterparts. In this article, we further explore why Blacks make that choice; in other words, we are examining those subcontexts that lead Blacks to prefer prison over alternative sanctions. To simplify comparisons as we delve deeper into the demographic and contextual predictors that help explain this decision, we operationalize preference for the alternative as an inmate’s willingness to serve more than 12 months of an alternative sanction rather than 12 months in a medium-security prison. In other words, any respondent who indicated they were willing to serve 13 or more months of any sanction was defined as having a preference for that alternative over prison. We realize that inmates are not technically given a choice between prison and some other alternative. Nevertheless, for expediency, when an inmate is willing to serve more than 12 months of the alternative, we say the inmate prefers that alternative over prison. Using this definition, we created four dichotomous dependent variables.

For each of the three alternatives (electronic monitoring, community service, and regular probation), respondents who answered 13 or higher were coded as 1, while those who answered 12 or lower were coded as 0. We then estimated logistic regression models predicting preference for regular probation, community service, and electronic monitoring over prison for the entire sample and separately for Black and White inmates in each table. We then created a dependent variable that identified respondents who preferred at least one of the three alternatives (electronic monitoring, community service, or probation) instead of prison. For this variable, respondents who answered 13 months or higher for electronic monitoring, community service, or regular probation were coded as 1, while those who answered 12 months or less for all three were coded as 0. Logistic regression results predicting preference for at least one alternative sanction over prison are presented in Table 5. As demonstrated in Table 2, a large majority of respondents (74%) preferred at least one of the three alternatives. The most popular alternative among respondents was regular probation at 49%, followed by community service at 35%, and finally electronic monitoring at 32%.4

Table 5.

Binary Logistic Regression Odds Ratios of Preference for Electronic Monitoring Over Prison.

	Model 1	Model 1W	Model 1B	Diff.a
Black	0.58*	—	—
Male	0.85*	0.72*	1.85*	p < .001
Educationb
Less than high school	0.90	0.93	0.82	NS
Attended college	1.15	0.97	2.01	NS
Age	0.97***	0.97**	0.98*	NS
Had job	1.09	1.27	0.83	NS
Responsibility for child(ren)b
Full-time	1.87**	1.87***	2.14*	NS
Part-time	1.31	1.48	0.99	NS
Childhood localeb
Medium city	1.50*	1.69*	1.42	NS
Small city/town/rural	1.13	1.28	0.85	NS
Exp. childhood poverty	1.33	1.22	1.79	NS
Mother’s educationb
Less than high school	1.07	1.14	0.87	NS
Attended college	1.17	1.44*	0.73	NS
Unknown	0.81	0.82	0.71	NS
Parent incarcerated	1.00	1.01	0.97	NS
Sibling incarcerated	0.72**	0.69***	0.74	NS
Uncle/aunt incarcerated	1.44þ	1.47	1.39	NS
Cousin incarcerated	0.94	0.93	0.96	NS
Pseudo-R2	0.06	0.06	0.07
n	1,024	719	305

Note. NS = not significant.

^aSignificance test for difference between Whites and Blacks.

^bReference categories: high school (education), no children (responsibility for children), large city/suburb (childhood locale), high school (mother’s education).

^þp < .10.

^*p < .05.

^**p < .01.

^***p < .001.

Table 2.

Descriptive Means/Proportions for Full Sample and by Race.

	All	White	Black	B-W Diff.
Preference
Regular probation	0.49	0.54	0.38	−0.16***
Community service	0.35	0.39	0.25	−0.14***
Electronic monitoring	0.32	0.35	0.25	−0.10**
At least one alternative	0.74	0.76	0.69	−0.07**
Background
Black	0.30	—	—	—
Male	0.75	0.70	0.86	0.16***
Education				ω2 = 2.53
Less than high school	0.27	0.28	0.26	−0.02
High schoola	0.53	0.51	0.57	0.06
Attended college	0.20	0.20	0.17	−0.03
Age	36.85	37.20	36.03	−1.17
Personal/family history
Responsibility for child(ren)				ω2 = 0.70
No childrena	0.25	0.26	0.25	−0.01
Full-time	0.21	0.22	0.20	−0.02
Part-time	0.53	0.53	0.55	0.02
Had job	0.61	0.61	0.62	0.01
Childhood locale				ω2 = 181.28***
Large city/suburba	0.32	0.20	0.58	0.38
Medium city	0.13	0.11	0.18	0.07
Small city/town/rural	0.55	0.69	0.24	−0.45
Exp. childhood poverty	0.49	0.45	0.59	0.14***
Mother’s education				ω2 = 24.11***
Less than high school	0.35	0.37	0.23	−0.14
High schoola	0.33	0.34	0.38	0.04
Attended college	0.22	0.19	0.29	0.10
Unknown	0.10	0.11	0.09	−0.02
Parent incarcerated	0.34	0.35	0.33	−0.02
Sibling incarcerated	0.46	0.42	0.55	0.13***
Uncle/aunt incarcerated	0.37	0.34	0.43	0.09*
Cousin incarcerated	0.39	0.34	0.49	0.15***
n	1,024	719	305

Note. Significant differences based on two-tailed t-test for numeric and dichotomous variables and ω² for variables with more than two categories.

^aReference category.

^*p < .05.

^**p < .01.

^***p < .001.

We focus on differences in preferences for correctional alternatives for White and Black respondents. Respondents who identified White as their only racial/ethnic identity were coded as White, but respondents who identified themselves as Black (including 18 respondents that mentioned Black as one of their racial or ethnic ancestries when they indicated they were multiracial) were coded as Black. The decision to include Black multiracial respondents in the Black category is supported by evidence highlighting that many multiracial individuals are identified as (and are perceived by others as) Black (James, 1991; Khanna, 2010), a phenomenon that finds its roots in the “one-drop” rule (Campbell, 2007; Khanna, 2010; Qian, 2004; Snipp, 2010). Respondents who did not provide a racial/ethnic identity (n = 34) or who did not fall into one of the two groups described above (n = 15) were excluded from the sample. Our analytic sample for this study is 1,024, of which 30% are Black and the remaining 70% are White.

We include three additional sociodemographic variables in our analysis: gender, educational attainment, and age. Males are coded as 1 and females as 0. Educational attainment is divided into three categories: less than high school, high school degree (reference category), and at least some college. We chose to use the high school degree as the reference category because approximately half of the inmates either had completed high school/general educational development prior to their incarceration or were able to do so while incarcerated. Age was calculated using respondents’ year of birth. Although three quarters of our sample are men, the ratio of men relative to women is higher among Blacks than among Whites. Blacks and Whites do not, however, differ significantly on education—just over half of the respondents have a high school degree and nearly one fifth have attended college among both groups. The average age for both Black and White respondents is around 37 years.

We also evaluated a number of characteristics related to respondents’ personal histories. The first two measures focus on the inmate’s life circumstances just prior to incarceration. One variable accounts for whether the respondent was employed (full-time or part-time) just before being incarcerated (yes = 1). The second was created using responses to two questions from a survey supplement, which was completed by respondents who had children. The first question asked whether the respondent’s child(ren) lived with the inmate just before their current incarceration. Answer options included (a) yes, on a full-time basis, (b) yes, on a part-time basis, and (c) no. A second question asked whether the respondent plans to live with their child(ren) when they are released. For this question, respondents could select (a) yes, right away, (b) yes, but not right away, or (c) no. We divided respondents who reported having children into two groups: (1) individuals with full-time responsibility for their children (answer option “a” for both questions) and (2) individuals with less than full-time responsibility for their children (answer options “b” or “c” for either question). We did so because we believed that respondents who both lived with their children before incarceration and planned to do so immediately upon release are more actively involved in their children’s lives and would thus have different perceptions about the incarceration experience than those respondents who either have no children or had children but are less involved in their lives. Respondents without children serve as the reference group.

The remaining variables capture respondents’ childhood experiences and family incarceration history. We included a childhood locale variable that is coded into three categories: (1) large cities (more than 250,000 people) and their suburbs (reference group), (2) medium cities (50,000 to 250,000 people), and (3) locales of 50,000 people or less (small city, town, and rural). We also included two commonly used measures of childhood socioeconomic status. The first measures whether the respondent’s family received public assistance while they were growing up (used as a proxy for childhood poverty), and the second measures their mother’s education (less than high school, high school, attended college, or unknown). Last, we believed that an inmate’s family incarceration history would have an important impact on their own perception of the punitiveness of prison and that this perception might vary by the closeness of their kinship relations with family that had been incarcerated. We include four dichotomous variables to account for whether the respondent has ever had an incarcerated parent, sibling, uncle or aunt, and cousin.

Analytical Strategy

We begin by reviewing racial variation in the preference for various alternatives in lieu of prison by looking at mean differences. Next, we use logistic regression to assess how personal background characteristics and personal history influence preferences for alternatives to prison. We also estimate separate models for Whites and Blacks to examine whether processes vary by race, noting statistically significant differences for each predictor. Models include robust standard errors to adjust for clustering at the institution level. Results are presented in the form of odds ratios. An odds ratio above 1 means that there is a positive relationship between the independent and outcome variables, while an odds ratio below 1 means that there is a negative relationship between these two variables.

Results

We begin with the most preferred alternative, regular probation. According to descriptive results from Table 2, White inmates are significantly more likely to prefer probation over prison than Black inmates (54% of Whites compared to 38% of Blacks). Table 3 presents odds ratios from multivariate models predicting the preference for probation over prison. Results from Model 1 show that even after accounting for social background and pre-incarceration history, Blacks have 40% lesser odds of preferring probation to prison than Whites. Male inmates are also less likely to prefer probation to prison than female inmates; however, this difference is only marginally significant. We also find that inmates with less than a high school degree and older inmates are less likely to prefer probation over prison. Conversely, inmates who lived in smaller locales (medium city or smaller) or experienced poverty as children have greater odds of preferring probation over prison than those who grew up in or around a large city or who did not experience poverty.

Table 3.

Binary Logistic Regression Odds Ratios of Preference for Regular Probation Over Prison.

	Model 1	Model 1W	Model 1B	Diff.a
Black	0.58*	—	—
Male	0.60þ	0.47**	1.37	p < .001
Educationb
Less than high school	0.64*	0.62**	0.62	NS
Attended college	1.19	1.22	1.11	NS
Age	0.98**	0.98**	0.98þ	NS
Had job	1.00	1.19	0.70	NS
Responsibility for child(ren)b
Full-time	1.38	1.38	1.59	NS
Part-time	1.34þ	1.37	1.29	NS
Childhood localeb
Medium city	1.64*	1.25	2.25*	NS
Small city/town/rural	1.47*	1.17	2.32***	p < .01
Exp. childhood poverty	1.42*	1.65**	1.03	NS
Mother’s educationb
Less than high school	1.11	1.10	1.21	NS
Attended college	1.13	1.27	0.93	NS
Unknown	0.75	0.83	0.55*	NS
Parent incarcerated	0.93	0.87	0.90	NS
Sibling incarcerated	1.00	1.12	0.78	p < .10
Uncle/aunt incarcerated	1.14	1.22	1.04	NS
Cousin incarcerated	0.82	0.80	0.83	NS
Pseudo-R2	0.06	0.05	0.05
n	1,024	719	305

Note. NS = not significant.

^aSignificance test for difference between Whites and Blacks.

^bReference categories: high school (education), no children (responsibility for children), large city/suburb (childhood locale), high school (mother’s education).

^þp < .10.

^*p < .05.

^**p < .01.

^***p < .001.

Racial subgroup estimates are presented in Table 3, Models 1W and 1B. While some of the factors described previously have similar effects on the preference for probation for Whites and Blacks, we also find some notable differences. For example, the marginally significant gender difference in the preference for probation over prison appears to be driven by a significant gender difference among Whites. Specifically, White males have less than half the odds of preferring probation over prison compared to White females. We find no significant gender difference among Blacks. Conversely, childhood locale only has a significant effect on the preference for probation over prison among Blacks. Black inmates who grew up in a large city or suburb are less likely to prefer probation than Blacks from smaller locales.

The results presented in Table 4 focus on the preference for community service, a more restrictive alternative than regular probation. Results from Table 4, Model 1, show that Blacks are also less likely to prefer community service over prison than Whites. Males also have lower odds of preferring community service over prison, as do older respondents. Conversely, respondents who grew up in medium-size cities have nearly twice the odds of favoring community service than those who grew up in large cities or their suburbs. Unlike the findings for the preference for probation, we do not find significant racial differences in the effect of gender on the preference for community service over prison. The positive effect of growing up in a medium city also extends to both racial groups; however, the magnitude of the effect is significantly larger for Blacks than for Whites.

Table 4.

Binary Logistic Regression Odds Ratios of Preference for Community Service Over Prison.

	Model 1	Model 1W	Model 1B	Diff.a
Black	0.53***	—	—
Male	0.67*	0.63*	0.77	NS
Educationb
Less than high school	0.90	0.87	1.04	NS
Attended college	1.19	1.27	0.86	NS
Age	0.98**	0.98**	0.98	NS
Had job	0.97	1.10	0.75	NS
Responsibility for child(ren)b
Full-time	1.27	1.34þ	1.27	NS
Part-time	1.15	1.38	0.66	p < .05
Childhood localeb
Medium city	1.90**	1.48*	2.58**	p < .05
Small city/town/rural	1.18	1.08	1.37	NS
Exp. childhood poverty	1.15	1.20	1.01	NS
Mother’s educationb
Less than high school	1.24	1.26	1.29	NS
Attended college	1.12	1.19	0.93	NS
Unknown	0.80	0.82	0.69	NS
Parent incarcerated	0.84	0.89	0.70	NS
Sibling incarcerated	0.93	0.87	1.09	NS
Uncle/aunt incarcerated	1.36	1.35	1.50	NS
Cousin incarcerated	0.91	0.83	1.17	NS
Pseudo-R2	0.05	0.03	0.07
n	1,024	719	305

Note. NS = not significant.

^aSignificance test for difference between Whites and Blacks.

^bReference categories: high school (education), no children (responsibility for children), large city/suburb (childhood locale), high school (mother’s education).

^þp < .10.

^*p < .05.

^**p < .01.

^***p < .001.

The results presented in Table 5 provide analyses for the most restrictive alternative to incarceration, electronic monitoring. As with the two previous alternatives, Blacks continue to have significantly lower odds of preferring electronic monitoring over prison (see Model 1). Similar to previous models, age is negatively associated with the preference for electronic monitoring, and inmates who grew up in a medium city are also more likely to prefer electronic monitoring over prison than those from large cities or their suburbs. In this model, however, children and family incarceration history emerged as significant predictors of preference for electronic monitoring over prison. Inmates with full-time responsibility for their children have nearly twice the odds of preferring electronic monitoring than inmates without children. Post- estimation tests confirm that those who have full-time responsibility are also significantly more likely to prefer electronic monitoring than parents who did not have full-time responsibility for their children (p < .05). In addition, having had an incarcerated sibling decreases the odds of preferring electronic monitoring to prison, whereas having had an incarcerated uncle or aunt results in a marginally significant increase in the odds of preferring electronic monitoring.

Once again, racial subgroup results are presented in Models 1W and 1B. Unlike previous models, we do not find a gender effect on the preference for electronic monitoring; however, a significant gender gap emerges for Black inmates. We find that Black males have nearly twice the odds of preferring electronic monitoring than Black women. We conducted additional analysis to investigate the possible source of this gender gap. Bivariate results show that among both Blacks and Whites, women are more likely to prefer electronic monitoring than men; however, in the multivariate model, the gap for Whites becomes insignificant, while the gap for Blacks reverses. This reversal appears to be related to the presence of children; however, the small number of Black women and even smaller number of Black women without children suggest that this reversal should be taken with extreme caution.

What factors influence the preference for at least one of these alternatives to incarceration over incarceration? Table 6 presents multivariate results from models predicting the preference for at least one of the three alternatives to prison. After accounting for background characteristics and pre-incarceration history in Model 1, we find that Blacks have lower odds than Whites of preferring at least one of these three alternatives to incarceration; however, this difference is only marginally significant. Other factors associated with the preference for at least one alternative over prison include the presence of children, experiencing poverty while growing up, and mother’s education. Specifically, we find that those inmates who have children (whether present full-time or part-time) have higher odds of preferring at least one alternative than those who do not. Similar patterns emerge for those who experienced childhood poverty and for those who grew up in a medium-size city (vs. large city or suburb). Inmates whose mother attended college have a marginally significant greater odds of preferring at least one of the three alternatives, whereas those who do not know their mother’s education have significantly lower odds of preferring at least one of the three alternatives.

Table 6.

Binary Logistic Regression Odds Ratios of Preference for at Least One of the Three Correctional Alternatives to Prison.

	Model 1	Model 1W	Model 1B	Diff.a
Black	0.64þ	—	—
Male	0.90	0.66**	1.69*	p < .001
Educationb
Less than high school	0.77	0.74*	0.77	NS
Attended college	1.17	1.29	0.95	NS
Age	0.99	0.98þ	1.00	p < .10
Had job	0.90	1.08	0.68	NS
Responsibility for child(ren)b
Full-time	1.64þ	1.24	3.22**	p < .10
Part-time	1.56***	1.45***	1.86*	NS
Childhood localeb
Medium city	1.38þ	1.60	1.24	NS
Small city/town/rural	1.24	1.21	1.37	NS
Exp. childhood poverty	1.55***	1.77***	1.29	NS
Mother’s educationb
Less than high school	1.06	1.36	0.68	NS
Attended college	1.37þ	1.43	1.13	NS
Unknown	0.61*	0.75	0.34	NS
Parent incarcerated	0.95	0.65*	1.70	p < .05
Sibling incarcerated	0.97	1.12	0.80	NS
Uncle/aunt incarcerated	1.13	1.24	0.97	NS
Cousin incarcerated	1.00	0.89	1.20	NS
Pseudo-R2	0.06	0.05	0.07
n	1,024	719	305

Note. NS = not significant.

^aSignificance test for difference between Whites and Blacks.

^bReference categories: high school (education), no children (responsibility for children), large city/suburb (childhood locale), high school (mother’s education).

^þp < .10.

^*p < .05.

^**p < .01.

^***p < .001.

Racial subgroup results from Table 6, Models 1W and 1B, also point to important differences in the effects of social background and personal history on the preference for at least one alternative over prison. For example, White males have significantly lower odds of preferring at least one alternative than White females, while Black males have significantly higher odds than Black females. To help reconcile racial differences in the effect of gender, we completed additional subgroup analysis (available upon request). Findings revealed that the gap between White men and White women was fairly consistent across bivariate and multivariate models, while the gap between Black men and Black women only emerged after accounting for the presence of children; thus, the gender gap for Blacks should once again be read with caution.

We also find significant racial differences in the effect of having children present full-time and of having had incarcerated relatives. Results for Whites show no significant difference in the preference for at least one alternative to prison between full- time parents and those without children. For Blacks, however, we find a substantial difference between full-time parents and those without children. Because the presence of children was so closely tied to the gender gap for Blacks, we analyzed similar models for White and Black men, but these models garnered nearly identical results. In the fully saturated model, the interaction between race and having children present full-time was large enough to close the racial gap in the preference for at least one of the three alternatives. This means that racial gaps in the preference for at least one alternative only hold among respondents who have no children or are part-time parents. Regarding family incarceration history, subgroup findings show that the effect of having an incarcerated parent differs for Whites and Blacks. Among Whites, having had an incarcerated parent reduces the odds of preferring at least one alternative over prison by 35%, but for Blacks, the effect of having an incarcerated parent is insignificant.

Discussion

Recent evidence emphasizes the financial burden of mass incarceration, rampant overcrowding of prisons, and ineffectiveness of long prison sentences for reducing recidivism, and policy-makers are turning to correctional alternative as possible solutions (PEW, 2009). While the burden of mass incarceration disproportionately impacts Black communities, Blacks remain less likely to support correctional alternatives to incarceration than Whites. This study goes beyond previous explorations of racial gaps in preferences for correctional alternatives over prison by evaluating how social background and pre-incarceration history differentially effect perceptions of alternative sanctions among White and Black inmates.

We found that certain factors predict preferences for regular probation, community service, and/or electronic monitoring for White and for Blacks, the most significant of which is age. Across all models, and for both Whites and Blacks, age is negatively associated with a preference for correctional alternatives compared to prison. It appears that as respondents grow older, they are less likely to prefer any of the three alternatives compared to prison. One reason may be that older respondents are more likely to be familiar with the criminal justice system and may thus be more skeptical of correctional alternatives.

We also find racial differences in the preference for each correctional alternative over prison; these differences remain largely unchanged in multivariate models that account for demographic characteristics, the presence of children, childhood experiences, and family incarceration history. In our combined models, these factors do not appear to explain or mediate the racial gaps in preferences for regular probation, community service, or electronic monitoring over prison; however, several other factors do appear to moderate the relationship between race and preferences for correctional alternatives over prison.

Childhood locale (urbanicity) has a significant impact on the preference for probation over prison. Although probation was the most acceptable alternative of the three, it was also the most polarizing, with just over a third of Blacks preferring regular probation as opposed to over half of Whites. Results suggest that these racial differences are primarily among respondents who grew up and, upon release, are still likely to live in large cities and their suburbs. The impact of urbanicity on Blacks’ preference for prison over probation is not surprising. African American males growing up in large, urban areas often have more negative interactions with police than their small town and rural counterparts. Young, Black males living in inner-city urban areas are more likely to have been hassled by police and are probably more likely to see their friends and relatives harassed by police and probation officers (Maguire & Pastore, 2008; Tuch & Weitzer, 1997; Weitzer & Tuch, 1999).

Youths growing up in urban inner-city areas have different experiences with probation as well. These areas often have active youth gangs in their neighborhoods. Gang members (and urban youths in general) are more likely to be supervised by probation officers, and a number of cooperative efforts between police and probation in many inner cities are designed to quell gang and firearm violence (Kennedy, 1996). Thus, inmates who grew up in these neighborhoods (whether they personally experienced probation or not) are more likely to have more negative opinions of probation officers than their smaller city and rural counterparts who have not had as much personal or vicarious experience with probation officers and the challenges of being successful on probation. Although not as distinct, the impact of childhood locale was also a factor for preference for community service over prison. No research, of which we are aware, has explored the intricacies of this relationship. Future research efforts should do so, given the strength of this finding and the general lack of success that Applegate (2014) had with other explanations for racial differences in preferences for prison over community sanctions.

Another important finding relates to the intersection of race and gender. Although previous studies have noted stark gender differences in preferences for correctional alternatives—as males are much more likely to choose prison over alternatives than females (see May & Wood, 2010, for review)—we find that these differences are more likely to occur among Whites than among Blacks. While White women are much more likely to prefer regular probation, and to a lesser extent community service, than White men, these differences are not evident in subgroup analysis for Blacks. In a similar manner as childhood locale, differences in the gender gap between Whites and Blacks are largest for the preference for regular probation over prison. This finding suggests that, like Black men, Black women may also be suspicious of the merits of regular probation over prison.

Respondents’ level of responsibility for their children also appears to play an important role in their preferences for correctional alternatives. Despite the relative loss of freedom that comes with electronic monitoring compared to regular probation and community service, respondents who reported having sustained full-time care of their children, regardless of race, were more likely than others to identify electronic monitoring as a possible alternative to incarceration. The presence of children was also important for predicting the preference for at least one alternative. Our findings demonstrate that having children part-time is equally important for Whites and Blacks. Findings also show that having children full-time has no effect for Whites but has a large impact on the preference for at least one alternative among Blacks. Moreover, these findings are not driven by the women in the sample (as we find similar results when focusing solely on men), nor are they driven by a small subgroup, as about one fifth of both White and Black respondents note having sustained full-time responsibility of their children. By suggesting that the presence of children is important, if not more important, for preferences for correctional alternatives among Blacks than among Whites, these findings challenge the prevailing narrative of Black men as absent or unengaged fathers found in the popular media but not supported in academic research. This finding also presents a rich area for future research, as there is little research to date that has explored the importance of fatherhood on perceptions of the punishment of prison.

Limitations

This study is not without limitations. First, the prisoners that provided data for this research were from only one state, and only those eligible for parole or release within 12 months of the data collection were surveyed. Thus, any generalization of these findings to prisoners outside of Kentucky, or even all prisoners in Kentucky, should be done with caution. Second, given the relatively small number of Black females in the sample, findings regarding gender differences for Blacks should be viewed with extreme caution. We are confident that future research efforts would develop similar findings, but those presented here should be viewed as exploratory at best.

Implications

In this study, we sought a better understanding of how sociodemographic and correctional indicators impact preferences for correctional alternatives among Blacks and Whites and whether these factors could help explain why Blacks are more likely than Whites to prefer prison over community sanctions. Findings confirm the importance of age on preferences for prison over community corrections—regardless of the respondent’s race, older inmates are less willing than younger ones to do community sanctions in lieu of imprisonment. In addition, we identify several factors that influence race differences in preferences for alternatives to incarceration, including childhood locale, gender, and active parenting. Our work offers an incremental increase in understanding race differences in perceptions of sanction severity and how sociodemographic and correctional indicators contribute to these differences. Such knowledge adds to the small body of work that aims to establish a theoretical and empirical framework for a valid continuum of criminal justice sanctions and offers more insight into Black skepticism regarding participation in alternative/noncustodial sanctions.

Biographies

Yasmiyn Irizarry is an Assistant Professor of African and African Diaspora Studies and a Faculty Research Associate in the Population Research Center at the University of Texas at Austin. Her recent work, which centers on race and ethnicity, educational inequality, social attitudes, and prejudice/discrimination, has appeared in outlets, including Sociology of Race and Ethnicity, Social Science Research, and Social Science Quarterly.

David C. May is a Professor and Criminology Program Coordinator in the Department of Sociology and Social Work at Mississippi State University. He has published numerous articles and books in the areas of responses to school violence, perceptions of the severity of correctional punishments, fear of criminal victimization, and weapon possession and use among adolescents.

Adrienne Davis is currently pursuing a PhD in Sociology at Mississippi State University. His research interests include race and stratification across a wide variety of social and educational contexts.

Peter B. Wood is a Professor of Sociology and Criminology in the Department of Sociology, Anthropology, and Criminology at Eastern Michigan University. His work has appeared in many refereed outlets, including; Justice Quarterly, Criminology, Journal of Research in Crime and Delinquency, among others.