Spatial Distance,Community Disadvantage,and Racial and Ethnic Variation in Prison Inmate Access to Social Ties

Abstract

Objectives:

This article examines the impact of distal prison placements on inmate social ties. Specifically, we test whether distance adversely affects inmates by reducing their access to family and friends and then test whether the effects are amplified for minorities and inmates who come from socially disadvantaged areas.

Methods:

These questions are assessed using a sample of inmates that includes all convicted felony offenders admitted to a single state’s prison system over a three-year period.

Results:

We find that inmates vary greatly in the distance from which they are placed from home and that Latinos are placed more distally than Blacks and Whites. We also find that distance and community disadvantage adversely affect the likelihood of inmate visitation. Although the adverse effect of distance appears to be similar across racial and ethnic groups, a difference exists among Blacks—for this group, high levels of community disadvantage amplify the adverse effects of distance.

Conclusions:

This study identifies an important dimension along which incarceration may adversely impact inmates, their families, and the communities from which they come, and how these effects may be patterned in ways that disproportionately affect minorities and prisoners from disadvantaged areas.

Keywords

incarceration spatial distance social ties race ethnicity disadvantage

Introduction

An increasingly large body of theory and research suggests that “get tough” policies, including expanded use of imprisonment, may harm offenders, families, and communities, and that the harms disproportionately affect the poor and minority groups (Alexander 2010; Clear 2009; DeFina and Hannon 2013; Wakefield and Uggen 2010; Western 2006). Accordingly, researchers have called for understanding the ways in which incarceration results in collateral consequences—that is, additional sanctions, impediments, or constraints that result from a felony conviction or incarceration—and how these may be racially and ethnically patterned (Massoglia 2008; Sampson 2011; Travis 2005; Western and Wildeman 2009). The importance of examining whether such consequences emerge within prison stems from studies that document the diverse effects that incarceration experiences can have on inmates and their families (Berg and Huebner 2011; Rose and Clear 2003; Western and Muller 2013; Wolff and Draine 2004).

Although scholars have called for investigation of what occurs “behind” prison walls, few studies have empirically examined the diversity of prison experiences and their effects on different segments of the inmate population (Mauer and Chesney-Lind 2002; Nagin, Cullen, and Jonson 2009; Cochran and Mears 2013). Mentally ill inmates, for example, may experience greater difficulty adjusting to prison (Felson, Silver, and Remster 2012). Younger inmates may experience greater difficulty navigating prison social hierarchies, and so be at greater risk of trauma and victimization (Wolff, Shi, and Siegel 2009; Wooldredge and Steiner 2014). Not least, minorities may be treated differently by prison officers (Ramirez 1983) or experience a greater range or intensity of deprivations (Adams 1992).

Here, we focus on a specific dimension of the prison experience—the distance that inmates reside from their home communities—that may have important consequences, and, in particular, may reduce inmates’ access to social ties outside the prison walls. Prisoners consistently report that separation from family and friends constitutes a primary fear and concern (Adams 1992; Hairston 1991; Lanier 1991; Liebling 1999). Indeed, only a small proportion of inmates receive visits during incarceration, which scholars speculate stems in part from families having to travel long distances to prison facilities (Christian 2005; Christian, Mellow, and Thomas 2006; Drago, Galbiati, and Vertova 2011; Fuller 1993; Mumola 2000; Tewksbury and DeMichele 2005). For inmates who are minority or come from disadvantaged neighborhoods, distance may constitute an especially significant barrier to maintaining social ties. Families, for example, may have fewer resources to enable travel.

The potential consequences of adversely affecting visitation go beyond inmate concerns about maintaining contact with family. Many studies have found that visitation is associated with inmate behavior and the chances of successful integration upon release (Duwe and Clark 2013; Lanier 1993; LeBel and Maruna 2012; Mears, Wang, and Bales 2014; Rose and Clear 2003; Wolff and Draine 2004). Visitation may reduce strain and increase social bonds, for example, and in turn reduce misconduct and recidivism and improve other reentry outcomes (Christian et al. 2006; Drago et al. 2011; Liebling 1999; Cochran 2012; Listwan et al. 2013).

Against this backdrop, the goal of this study is to contribute to research aimed at understanding prisoner experiences and their potential to have far-reaching implications for individuals, families, and communities. At the same time, and in response to calls to examine how mass incarceration contributes to inequality (Sampson 2011; Western 2006), it seeks to illuminate how racial, ethnic, and socioeconomic differences may pattern the incarceration experience. In particular, we examine whether spatial distance may exert harmful effects by reducing visitation. We test the argument that minorities are placed more distally from home, as compared to Whites, and that distal placements may reduce more strongly their likelihood of being visited. We test as well the argument that such placements may reduce visitation more so among inmates who come from disadvantaged communities. Finally, we investigate the corollary of these two arguments—namely, the possibility that distance more strongly reduces visitation among Black and Latino inmates who come from disadvantaged communities. Implications of the study for understanding punishment and inequality are discussed.

Background

Mass Incarceration and Collateral Consequences

Despite the large-scale growth of imprisonment, research on the effects of imprisonment remains at an early stage of development. Few rigorous assessments of imprisonment effects on recidivism exist, for example, and many of them have identified null or iatrogenic effects (Nagin et al. 2009; Travis, Western, and Redburn 2014). In addition, although some studies suggest that large-scale imprisonment has reduced crime (e.g., Spelman 2006), other work suggests it has increased crime or created harms through adverse effects on ex-prisoners, families, and communities (e.g., Clear 2009; DeFina and Hannon 2013; Travis et al. 2014; Western and Muller 2013). In addition, scholarship indicates that minorities and economically disadvantaged groups experience these costs more acutely than their White and more advantaged counterparts (see, e.g., Foster and Hagan 2009; Hagan and Dinovitzer 1999; Mauer and Chesney-Lind 2002; Wakefield and Uggen 2010; Western 2006). This work underscores the salience of examining not only the diverse ways in which various harms may accompany incarceration but also how they may be racially or ethnically patterned (Sampson 2011).

When harms of punishment stem from conditions of inmates’ confinement, they might be viewed as the inherent “pains” of imprisonment that inmates face (Sykes 1958). However, some harms are not necessarily intrinsic to incarceration or need necessarily result from it. Scholars have referred to such harms as collateral consequences (or, when the harms expressly entail a form of sanction, as “invisible punishments”). For example, studies of employment and labor markets indicate that incarceration reduces the employability of ex-prisoners, which can lead to additional problems, such as homelessness (Pager, Western, and Bonikowski 2009; Petersilia 2005; Travis 2005). Inmates are also more likely to contract communicable diseases in prison and, upon release, to face significant barriers to accessing quality health care (Binswanger, Krueger, and Steiner 2009; Lee et al. 2014; Massoglia 2008; Visher and Travis 2003).

Here, we focus on reduced visitation as a type of collateral consequence. As we describe subsequently, visitation has been linked consistently, across qualitative and quantitative analyses, to a range of benefits for inmates, ex-prisoners, and their families. In most states, visitation constitutes a privilege, not a right. Inmates typically have access to visitation, but visitation itself is rare (Christian 2005; Cochran 2014; Petersilia 2005). When, therefore, prisons operate in ways that reduce visitation or when specific groups are less able to be visited, an additional consequence, or punishment, occurs and involves not only the inmate but also families and communities (e.g., Arditti and Keith 1993; Geller et al. 2009, 2012; Hagan and Dinovitzer 1999).

Reduced visitation can contribute, among other things, to severed social ties and erosion of social support networks. Indeed, research implicates visitation and social ties to communities as an integral part of the incarceration experience that affects in-prison and post-release behavior (Arditti 2012; Bales and Mears 2008; Comfort 2008; Wakefield and Uggen 2010). For example, visitation during incarceration has been linked to reductions in recidivism likelihoods across different states and ex-prisoner samples (e.g., Duwe and Clark 2013; Mears et al. 2012).

In addition, research suggests that separation from family and friends constitutes one of the most feared and strainful aspects of the prison experience (Adams 1992; Liebling 1999; Sykes 1958). Separation is part and parcel of the prison experience; virtual separation is not. Even so, many inmates are never visited. Research suggests that the end result is a higher likelihood of poor in-prison and post-release outcomes (Bales and Mears 2008; Derkzen, Gobeil, and Gileno 2009; Duwe and Clark 2013; Mears et al. 2012; Monahan, Goldweber, and Cauffman 2011; cf. Siennick, Mears, and Bales 2013).

Explanations for visitation effects vary. Theoretical and empirical accounts emphasize the salience of social bonds—and their activation through visitation—to buffer the harmful effects of stigmatization and labeling (Cochran 2014; Mears et al. 2012). Social ties that extend outside the prison walls may assist inmates in negotiating prison life and reentry through the social capital and support available from them (see, generally, Berg and Huebner 2011; Casey-Acevedo and Bakken 2002; Hairston 1991; Holt and Miller 1972; LeBel and Maruna 2012; Visher 2013). By contrast, inmates who feel more isolated have greater difficulties adjusting to prison, are at a heightened risk for mental illness, and engage in more misconduct, violence, and self-injurious behavior (Clemmer 1940; Liebling 1999; Rhodes 2004; Thoits 1983).

The Implications of Spatial Distance for Inmate Access to Social Ties

Many factors contribute to reduced visitation. A range of studies have found, for example, that inmates’ family and friends struggle to travel to prison facilities (Christian 2005; Christian et al. 2006; Comfort 2003; Jackson et al. 1997; Monahan et al. 2011; Tewksbury and DeMichele 2005; Visher 2013). Reliance on public transportation is one reason. Research has identified other barriers, however, that parallel those faced by individuals seeking medical or social services (Andersen 1995). Some barriers include the need to take time off from work, pay fees, and find child care. Apart from these logistical challenges, there are practical ones as well, including the challenge of learning how to navigate the complex administrative rules and regulations related to visitation privileges (Arditti 2003; Christian et al. 2006; Comfort 2003).

Of all the barriers visitors might encounter, the distance between a facility and an inmate’s home community may be the most salient (Baunach 1985; Christian et al. 2006; Coughenour 1995; Hairston 1991; Koban 1983; Lanier 1991, 1993). Research on the experiences of prisoners and their families emphasize logistical travel challenges individuals face when attempting to visit inmates. Distance is explicitly and frequently mentioned by inmates and their visitors as an impediment to visitation (Christian 2005; Christian et al. 2006; Fuller 1993; Tewksbury and DeMichele 2005). National estimates suggest that inmates are housed on average more than 100 miles from their last place of residence (Mumola 2000). Longer distances create a potential cascade of challenges and costs, such as arranging to take time off from work and paying for babysitters, fuel, transportation, and lodging (Christian 2005; Tewksbury and DeMichele 2005).

Minorities, Community Disadvantage, and Spatial Distance

To the extent that spatial distance contributes to social distance, the effect is likely to be most pronounced among disadvantaged populations. Many inmates, minorities in particular, come from highly impoverished communities. These individuals and their families typically will lack the resources necessary for overcoming logistical barriers to visitation, such as the need to take time off from work and, in some instances, to secure child care, to have a vehicle or ready access to public transportation, and to have the financial ability to pay for gas and lodging (Mauer and Chesney-Lind 2002; Travis 2005). Similar barriers arise for minorities in securing employment or accessing welfare benefits (Edin and Lein 1997; Visher and Travis 2003; Western 2006). Wilson (1996), for example, has documented a myriad of obstacles disadvantaged and minority groups face when seeking transportation to job opportunities located outside of their neighborhoods (see also Edin and Lein 1997; Golub, Marcantonio, and Sanchez 2013; Sanchez, Shen, and Peng 2004; Wilson 1987). Similarly, research has shown that without subsidies for transportation or child care, low-income populations have difficulties obtaining gainful employment (Corcoran et al. 2000; Danziger 2010). More broadly, this work has highlighted the potential for poverty and community disadvantage to amplify barriers that arise for minorities (Pager et al. 2009; Wang et al. 2013). For example, Blacks on average have fewer financial resources on which to draw and reside in areas that are spatially isolated in ways that make finding work or child care even more difficult (Sampson 2009; Wilson 1996).

In short, spatial distance and other obstacles to work or child care not only may be more prevalent among minorities and those who reside in disadvantaged communities, the effects of these obstacles also may be greater. Minorities, for example, typically will be more likely to reside in inner-city communities (Wilson 1996) and thus to be less proximate to state-run prisons. In addition, the greater rate of poverty among minorities implies that logistical challenges may be more difficult to overcome and so further reduce the likelihood of visitation.

This Study

The focus of this study is on the implications of spatial distance for inmate social ties. To this end, it examines several interrelated lines of investigation: the possibility that minorities and inmates from disadvantaged communities on average reside more distally from their home communities, that such placements reduce visitation, and that minorities from disadvantaged communities are more likely to be adversely affected by them.

Analytic Strategy

To investigate the role of spatial distance on visitation, the analyses proceed in several stages and rely on data on Florida prisoners. First, we discuss the descriptive statistics for the study variables, which include a series of figures and maps. The focus here centers on distance, visitation, and the distribution of the two across different racial and ethnic groups, and also across geographic regions of Florida. Second, we use hierarchical logistic regression analysis to control for potential confounding and to examine the effect of distance, race and ethnicity, and disadvantage on the likelihood of inmate visitation. Third, we use hierarchical logistic regression to test whether distance and disadvantage effects on visitation are conditioned by race and ethnicity. Fourth, we employ similar regression analyses to test for multiplicative effects of race, ethnicity, disadvantage, and distance on visitation.

Data

The data for this study were provided by the Florida Department of Corrections (FL-DOC) and come from a cohort of prisoners admitted to Florida prisons between November 2000 and April 2002 (N = 34,941). A unique and useful characteristic of these data is that the inmate population in Florida includes a substantial proportion of Latinos, which provides opportunities to differentiate distance patterns and effects by both race and ethnicity. In addition, FL-DOC provided facility movement records for all inmates included in the cohort, which allowed us to identify county centroid-to-centroid distances and to account for facility transfers for all inmates. A small number of inmates in the sample spent all, or the majority of, their time in prison in an intake facility. Visitation, however, is typically not allowed in the initial period of incarceration while inmates are held in intake locations. To account for this issue and for the possibility that inmates incarcerated for too short of a period of time are unlikely to be visited, we excluded any inmates who spent less than two months in prison, which resulted in 826 cases being dropped. The final analysis sample included 34,115 admitted inmates.

Dependent Variable

The dependent variable used in the following analyses is a dichotomous measure of inmate visitation. Visitation data were collected by the FL-DOC. All visitation events for the inmates admitted during this time period were recorded via an automated system called Offender-Based Information System (OBIS). Inmates who were visited over the course of their incarceration term were coded as 1, and non-visited inmates were coded as 0. (As described subsequently, we also examined a series of ancillary analyses using a count measure of visitation.)

Independent Variables

The primary independent variable is the distance between the facility an inmate was housed in and their home community. Because inmates may be transferred between facilities during incarceration, this measure consists of the weighted average distance, including all prison placements and the duration of time spent at each, an inmate was located from their home community. Creation of this measure was possible because FL-DOC provided information about the county of conviction for all incarcerated offenders and facility movement records that indicate the amount of time inmates served in different facilities over the course of their prison terms. Using a publicly available county centroid distance matrix, provided by the Center for Transportation Analysis (http://cta.ornl.gov/cta), we calculated the highway mileage between each facility’s county centroid and the county centroid for an inmate’s county of conviction.

To create the weighted average measure, we calculated a “mile-days” value for every facility placement an inmate experienced. The mile-days value corresponds to the number of miles a given facility was located from an inmate’s home community, multiplied by the number of days spent in that facility. Second, we summed the mile-days values across the incarceration period for each inmate. Third, we then divided the summed mile-days value by the total number of days spent in prison. For example, if an inmate serves 100 days in prison, 50 of which are spent 1 mile away and 50 of which are spent 100 miles away, they would have an average weighted distance value of 50.5 [((50 days × 1 mile) + (50 days × 100 miles))/100 = 50.5], which reflects the average number of miles the inmate was placed from their home community during their term of incarceration. Inmates in Florida first enter into an intake facility before placement in an actual prison facility occurs. Visitation cannot occur while inmates are held in intake. Thus, we exclude time spent in intake facilities from the above calculation of inmates’ weighted average distance values. To facilitate interpretation of the results, the distance measure was divided by 10; coefficients thus can be interpreted as the effect of 10-mile increases in distance. (We tested the robustness of the distance effect by examining an unweighted distance measure for those inmates—approximately 18 percent of all inmates—who stayed in a single prison for the duration of their incarceration term. The results were substantively the same as those presented below).

To test the association between contextual disadvantage and visitation, we created two county-level disadvantage measures, one using general population measures and three others that were White-, Black-, and Latino-specific. No single unit of analysis best captures the social context from which inmates come. Here, following the lead of prior studies, we employ counties to examine how context may influence the likelihood that an inmate’s family, friends, and community members will have the resources to visit inmates. These measures are consistent with county-level indices used previously (e.g., Land, McCall, and Cohen 1990; Steffensmeier et al. 2010; Wang et al. 2010). In keeping with this research, we use race- and ethnicity-specific measures and models to test for potential interactional effects of distance and context on social support access. This approach accords with research on racial and ethnic stratification that highlights the marked differences in the social contexts of racial and ethnic groups (Krivo and Peterson 2000; see also, Alba, Logan, and Bellair 1994; Mears et al. 2014; Western 2006). For each index, we used four measures from the 2000 U.S. Census: percentage of female-headed households, percentage below the poverty line, percentage without a high school diploma, and median household income. To test the robustness of the results, we explored a range of alternative model specifications, which incorporated other county-level measures, such as population density, urbanicity, and economic inequality. In each instance, the measures were not significantly associated with visitation and no appreciable difference, statistically or substantively, surfaced in the association between distance and visitation when compared to the results discussed below.

Control Variables

FL-DOC data include a wide range of measures of pre-prison characteristics that can be used to control for potential confounding influences on the relationship between distance and visitation. Few prior studies systematically examine the factors related to visitation and inmate placement distance (see, however, Cochran, Mears, and Bales 2014; Drago et al. 2011; Jackson et al. 1997; Tewksbury and Connor 2012). Nonetheless, we incorporate factors that might confound estimation of the distance–visitation association. Specifically, the models include dichotomous measures of sex (male = 1, female = 0), dummy variable coding for race and ethnicity (White, non-Latino, Black, non-Latino, and Latino), and a continuous measure of age. The models also control for prior record using a count of prior prison commitments, a count of sentence length (in months), a count of prior convictions, and dichotomous measures for five primary offense types: violent, sex, property, drugs, and other. To account for differences between inmates in opportunities to be visited, we also include a measure of time spent in prison (in months). In all of the analyses, non-Latino Whites and drug offenses serve as reference categories for race and ethnicity and type of offense, respectively.

Findings

Distance, by Race and Ethnicity

Table 1 provides descriptive statistics for the full sample and then separate descriptive statistics for White, Black, and Latino inmates. In accordance with prior studies (e.g., Bales and Mears 2008), we can see that a relatively low proportion of inmates—26 percent—are visited at least once during the course of incarceration. Visitation is higher among Whites and Latinos (32 percent) and lowest among Blacks (20 percent).

Table 1.

Descriptive Statistics.

	Total (n = 34,115)		White (n = 13,552)		Black (n = 17,418)		Latino (n = 3,145)
	Mean	SD	Mean	SD	Mean	SD	Mean	SD
Distance	204.83	129.91	194.84	117.72	206.01	131.58	241.42	160.31
Visited (1/0)	0.26	0.44	0.32	0.47	0.20	0.40	0.32	0.47
Male (1/0)	0.92	0.28	0.90	0.30	0.92	0.27	0.96	0.19
White (1/0)	0.40	0.49	—	—	—	—	—	—
Black (1/0)	0.51	0.50	—	—	—	—	—	—
Latino (1/0)	0.09	0.29	—	—	—	—	—	—
Age	31.99	10.02	33.38	10.10	31.03	9.77	31.33	10.33
Prior commitments (#)	0.96	1.51	0.69	1.22	1.28	1.73	0.40	0.87
Sentence length (mos.)	59.19	94.25	56.35	89.29	59.94	97.07	67.31	98.63
Prior convictions (#)	5.90	6.98	5.91	7.60	6.29	6.64	3.66	5.42
Offense—violent (1/0)	0.25	0.43	0.25	0.43	0.24	0.43	0.31	0.46
Offense—sex (1/0)	0.06	0.24	0.09	0.28	0.04	0.19	0.08	0.28
Offense—property (1/0)	0.29	0.45	0.36	0.48	0.23	0.42	0.30	0.46
Offense—drugs (1/0)	0.29	0.45	0.17	0.37	0.40	0.49	0.22	0.42
Offense—other (1/0)	0.11	0.31	0.13	0.34	0.09	0.29	0.08	0.28
Time served (mos.)	16.17	6.77	15.80	6.75	16.35	6.75	16.79	6.87
Disadvantage (z)	0.00	0.86	−0.11	0.76	0.30	1.03	0.03	0.88
White disadvantage (z)	—	—	0.00	0.77	—	—	—	—
Black disadvantage (z)	—	—	—	—	0.00	0.78	—	—
Latino disadvantage (z)	—	—	—	—	—	—	0.00	0.73

Note. mos. = months; SD = standard deviation.

Inspection of the table indicates that inmates in Florida on average are housed 205 miles from home. Using the rough approximation that 50 miles corresponds to one hour of travel, this finding suggests that, for a given inmate in Florida, visitors have to travel roughly four hours each way, amounting to a total of eight hours round-trip. The estimate likely is conservative, given that many inmate families and their friends may rely on public transportation to visit. In such cases, transportation times increase.

As further inspection of the table reveals, Blacks are housed, on average, only slightly farther away from home than Whites (206 vs. 195 miles, respectively). By contrast, Latinos are housed substantially farther away from their home communities than are Whites or Blacks. Specifically, they reside, on average, 241 miles from home—35 miles farther away than Blacks and 47 miles farther away than Whites. An analysis of variance (ANOVA) test indicated that the identified race and ethnic differences are statistically significant (F-test = 166.03, p < .05). However, as noted above, it is Blacks, not Latinos, who experience the lowest rates of visitation.

Figure 1 includes a series of “heat” maps of Florida, which extend the analysis above by identifying spatial patterns that may contribute to racial and ethnic placement disparities. The figure includes multiple panels. We start with panel A, which presents a map of state prison capacity (in 2001) to determine whether any spatial patterns emerge. Darker shades indicate greater prison capacity. Inspection of the map reveals that the central and northern counties in the state hold substantially more inmates, as indicated by the darker overall shading in the central and northern counties, than do counties in the southern tip of the state (e.g., the Miami-Dade region). For example, eight counties are identified with prison capacities of 1,800 inmates or more. Only two of these counties are located in the southern region of the state. Furthermore, the northern region uniformly has darker shading across its counties than southern counties, indicating overall greater prison capacity in those areas.

Figure 1.

Maps of Florida prison capacity (panel A), average placement distance (panel B), and inmates’ county of origin, by race and ethnicity (panels C, D, and E).

The clustering of state prisons in central and northern counties suggests that distal prison placements may be more likely among inmates from southern Florida. Support for this possibility can be seen in panel B, which includes a map indicating average inmate placement distance for inmates originating from a given county. The dark gray and black shades in southern counties indicate that when individuals from the southern region of the state are incarcerated, they on average are housed substantially farther away from their home communities than are inmates from more northern counties. We found that seven counties have average placement distances greater than 250 miles, all seven of which are located in the southern most region of the state.

Based on the findings identified above, we can anticipate that, to the extent a given racial or ethnic group is clustered in the southern region of the state, such a group will experience disproportionately more distal facility placements. Panels C, D, and E assess whether such a pattern emerges by examining the percentages of Latino, Black, and White inmates, respectively, originating from a given county in Florida. Darker shades indicate that a higher percentage of inmates of a given racial or ethnic group resided in a county prior to incarceration. At least two key patterns emerge. First, we see in panel C that clustering indeed occurs for Latino inmates. More than 15 percent of Latino inmates originate from a single county in southern Florida—specifically, 31 percent of Latino inmates originate from Miami-Dade County. Second, panels D and E highlight that Black inmates and White inmates, respectively, are relatively uniform in their contribution to state prison placements across counties. For Whites in particular, no county contributes more than 8 percent of White inmates to the state prison system. This spatial patterning in the racial and ethnic distribution of inmates, and also in the capacity of the prison system, likely contributes to the more distal prison placements experienced by Latino inmates (discussed further, below).

Distance and Visitation, by Race and Ethnicity

We now examine whether distance is associated with visitation and whether minority inmates and those from disadvantaged areas are less likely to be visited. Doing so constitutes a logical prior step to assessing whether race, ethnicity, and disadvantage condition potential distance effects. Figure 2 examines the bivariate relationship between distance and the percentage of inmates visited that are White, Black, or Latino. The figure suggests strong support, across all three groups, for a negative relationship between spatial distance and the likelihood of visitation—that is, for each group we observe lower probabilities of visitation as distance increases. There are differences, however, in the relative probabilities of visitation across racial and ethnic groups. For example, within 50 miles, or two hours of roundtrip travel, Latinos have the highest probability of visitation (52 percent), followed by Whites (47 percent) and by Blacks, who have the lowest probability of visitation (35 percent). Notably, across all distance categories, Blacks have a substantially lower probability of visitation.

Figure 2.

Percentage of inmates visited, by distance categories, by race and ethnicity.

Table 2 includes four hierarchical logistic regression analyses of visitation regressed on covariates. Model 1 estimates the association between only distance and visitation. Here, the significant, negative coefficient (−.042) suggests that distance is negatively associated with the likelihood of visitation.

Table 2.

Hierarchical Logistic Regressions of Prison Visitation on Distance, Pre-prison Individual Characteristics, and County-level Disadvantage.

	Model 1			Model 2			Model 3			Model 4
	b	OR	SE	b	OR	SE	b	OR	SE	b	OR	SE
Fixed effects
Intercept	−0.246***	0.782	0.033	−0.519***	0.595	0.084	0.069	1.071	0.086	0.301**	1.351	0.092
Individual level
Distance (/10 miles)	−0.042***	0.959	0.001	—	—	—	−0.047***	0.954	0.001	−0.072***	0.930	0.004
Distance²	—	—	—	—	—	—	—	—	—	0.001***	1.001	0.000
Male	—	—	—	−0.126**	0.882	0.047	−0.101	0.904	0.049	−0.101	0.904	0.049
Age	—	—	—	−0.037***	0.964	0.002	−0.035***	0.966	0.002	−0.035***	0.965	0.002
Black	—	—	—	−0.769***	0.464	0.031	−0.783***	0.457	0.032	−0.788***	0.455	0.032
Latino	—	—	—	−0.107*	0.899	0.048	−0.033	0.968	0.049	−0.049	0.952	0.049
Prior commitments	—	—	—	−0.225***	0.798	0.014	−0.218***	0.804	0.014	−0.219***	0.803	0.014
Sentence length	—	—	—	−0.001***	0.999	0.000	−0.000***	1.000	0.000	−0.001***	0.999	0.000
Prior convictions	—	—	—	0.013***	1.013	0.002	0.013***	1.013	0.002	0.013***	1.013	0.002
Offense—violent	—	—	—	−0.248***	0.781	0.038	−0.224***	0.799	0.039	−0.219***	0.803	0.039
Offense—sex	—	—	—	−0.497***	0.609	0.062	−0.448***	0.639	0.064	−0.443***	0.642	0.064
Offense—property	—	—	—	−0.335***	0.716	0.037	−0.337***	0.714	0.038	−0.334***	0.718	0.038
Offense—other	—	—	—	0.106*	1.113	0.047	0.123**	1.131	0.048	0.129**	1.137	0.048
Time served	-	-	-	0.086	1.090	0.002	0.094***	1.099	0.002	0.094***	1.099	0.002
County level
Disadvantage	—	—	—	0.023	1.023	0.031	−0.038	0.963	0.024	−0.041	0.960	0.024
Random effect
County variance	0.022		0.008	0.026		0.009	0.014		0.006	0.014		0.006

Note. White and offense—drugs serve as reference categories. n = 34,115. OR = odds ratio; SE = standard error.

***p < .001.

**p < .010.

*p < .05.

In model 2, we exclude distance and examine the potential effects on visitation of inmates’ pre-prison characteristics, time served, and a county-level measure of economic disadvantage. In model 3, distance and these covariates are included simultaneously to test whether a distance–visitation relationship emerges even after controlling for these factors. We find, in line with existing studies (e.g., Jackson et al. 1997), that several factors are associated with visitation. These include age, gender, race, ethnicity, and prior record. We find, too, that Blacks and Latinos are significantly less likely to be visited than are Whites, although the estimated effect for Blacks is substantially greater. This finding implies support for the argument that minority groups, Blacks in particular, may face greater challenges overcoming structural barriers to visitation. We also find that more serious offenders, including those with more prior prison commitments and those who have committed violent and sex crimes, are less likely to be visited. Contrary to what we anticipated, the race- and ethnicity-neutral disadvantage measure does not yield a statistically significant relationship with visitation.

Model 3 indicates that the distance effect holds after accounting for potential confounders. In addition, we find that, after accounting for distance, the majority of the coefficients from model 2 remain statistically significant, including those for age, race, and prior record. However, we find that after controlling for distance, ethnicity is no longer statistically significant. This finding accords with the bivariate analyses and suggests that Latinos have a lower likelihood of visitation and that this effect stems from more distal prison placements.

Finally, model 4 tests whether distance has a nonlinear effect; the nonlinearity was suggested by the curvilinear association in Figure 2. The coefficient for the quadratic term is positive and statistically significant and suggests a diminishing adverse effect of distance on visitation. That is, as inmates get farther away from home, the negative effect of 10-mile increases in distance on the likelihood of visitation diminishes. In the interaction analyses that follow, we illustrate this pattern graphically.

We also conducted a series of ancillary analyses, including a focus on visitation counts. A visitation count analysis addresses a conceptually distinct research question, one focused on whether spatial distance influences how many times inmates were visited, as opposed to simply whether inmates were visited at all. It is possible, for example, that distance influences most strongly the likelihood of the first visits but exerts a limited effect on the likelihood of experiencing many visits. In our sample, however, visited inmates typically received no more than a handful of visits—50 percent received four visits or less. Nonetheless, we conducted multilevel negative binomial regression modeling using Stata’s xtnbreg command, which accounts for overdispersion caused by a high frequency of zero visit counts in the sample, and assessed the impact of spatial distance on visitation counts. The results of these models identified effects that paralleled the estimated effects of the likelihood of any visitation. For example, for the full sample, coefficient estimates indicated a statistically significant, nonlinear, and visitation-reducing effect of distance. As with the analyses presented here, the estimated effect of distance declines at farther distances (distance = −0.0635, p < .001; distance² = 0.0004, p < .001). We also examined the same model using zero-inflated negative binomial regression; coefficient estimates for distance were nearly identical. Predicted count estimates based on the negative binomial regression results indicated that the average inmate placed 100 miles from home receives 2.4 visits, 250 miles from home receives 1.2 visits, and 400 miles from home receives .75 visits. We conducted parallel sets of count analyses for each of the models presented below and identified substantively identical findings in each instance (available upon request). The fact that distance–visitation associations appear to be similar across the analyses suggests that different processes are not involved in generating the binary outcome (visited or not) and the count outcome (repeated visits), respectively. This finding is of interest because it suggests that distance effects are in a sense absolute—that is, they create a barrier to visitation that exists regardless of prior visitation events.

The findings to this point indicate that Blacks and Latinos are less likely to be visited and that distance is associated with a lower likelihood of visitation. We now turn, in Table 3, to a test of the hypothesis that the effect of distance is greater among Blacks and Latinos. Here, we analyze each racial and ethnic group separately and, in each model, include the distance and distance-squared measures, pre-prison individual characteristics, time served, and race- and ethnicity-specific measures of disadvantage. For each group, we find statistically significant effects for distance and distance², with similar coefficient sizes, suggesting that the curvilinear distance effects are no different among these three groups. Ancillary analyses using two-way interaction terms (e.g., White × distance, Black × distance, Latino × distance) in a similarly specified model revealed substantively similar results.

Table 3.

Hierarchical Logistic Regressions of Prison Visitation on Distance, Pre-prison Individual Characteristics, and County-level Disadvantage, by Race and Ethnicity.

	White (n = 13,552)			Black (n = 17,418)			Latino (n = 3,145)
	b	OR	SE	b	OR	SE	b	OR	SE
Fixed effects
Intercept	0.717***	2.049	0.128	−1.037***	0.355	0.137	0.036	1.037	0.310
Individual level
Distance (/10 miles)	−0.071***	0.932	0.006	−0.072***	0.931	0.006	−0.081***	0.923	0.010
Distance²	0.001***	1.001	0.000	0.001***	1.001	0.000	0.001***	1.001	0.000
Male	−0.348***	0.706	0.065	0.299***	1.349	0.083	−0.013	0.987	0.214
Age	−0.040***	0.961	0.002	−0.028***	0.972	0.003	−0.038***	0.962	0.005
Prior commitments	−0.194***	0.824	0.022	−0.248***	0.780	0.019	−0.256***	0.774	0.069
Sentence length	−0.001**	0.999	0.000	0.000	1.000	0.000	−0.001	0.999	0.000
Prior convictions	0.009**	1.009	0.003	0.016***	1.016	0.004	0.033***	1.034	0.009
Offense—violent	−0.242***	0.785	0.065	−0.179***	0.836	0.055	−0.304*	0.738	0.122
Offense—sex	−0.447***	0.639	0.090	−0.392***	0.676	0.113	−0.554**	0.574	0.183
Offense—property	−0.397***	0.672	0.060	−0.275***	0.760	0.056	−0.362**	0.696	0.122
Offense—other	0.036	1.037	0.074	0.282***	1.326	0.069	−0.085	0.918	0.176
Time served	0.095***	1.100	0.003	0.091***	1.095	0.003	0.113***	1.120	0.007
County level
White disadvantage	−0.076*	0.927	0.034	—	—	—	—	—	—
Black disadvantage	—	—	—	0.006	1.006	0.030	—	—	—
Latino disadvantage	—	—	—	—	—	—	−0.253***	0.777	0.072
Random effect
County variance	0.018		0.008	0.005		0.006	0.019		0.018

Note. Offense—drugs serves as reference category. OR = odds ratio; SE = standard error.

***p < .001.

**p < .010.

*p < .05.

Figure 3 includes a plot of the likelihood of visitation, by distance, for Whites, Blacks, and Latinos, based on the estimates from the three models in Table 3. Recall that the distance–visitation association is not significantly different among the three groups. We present each group separately, however, to highlight the disparities in visitation by race and ethnicity. The plot parallels the probabilities shown in Figure 2. For each group, distance yields strongest effects on visitation likelihoods within the first 400 miles, after which increases in distance result in only a slightly reduced likelihood of visitation. However, the figure also reinforces the finding that Blacks, compared to Whites and Latinos, have a lower likelihood of visitation at any distance. For example, at 100 miles from home, roughly four hours of driving roundtrip, the predicted likelihood of visitation is highest for Latinos (43 percent), second highest for Whites (39 percent), and lowest for Blacks (24 percent).

Figure 3.

Predicted likelihood of visitation, by distance, by race and ethnicity.

A central question of focus in this study is whether inmates from disadvantaged areas have a lower likelihood of visitation. Inspection of Table 2 identified no such effect, but used a general measure of disadvantage. Table 3 revisits the question by employing race- and ethnicity-specific measures of disadvantage. Here, we find that disadvantage in fact is negatively associated with visitation among Whites and Latinos, but not among Blacks. That is, we find that White and Latino inmates, who come from counties with greater levels of White or Latino disadvantage, respectively, are less likely to be visited.

Figure 4 provides an illustration of the coefficients of race- and ethnicity-specific disadvantage, based on models estimated in Table 3. Among Latinos, a pronounced association between disadvantage and visitation can be seen. The probability of visitation among Latino inmates who come from areas of low economic disadvantage (2.5 standard deviations below the mean) is 37 percent. By contrast, the probability of visitation among Latinos in highly disadvantaged areas (2.5 standard deviations above the mean) is 19 percent. The effect among Whites is more subtle. In the least disadvantaged areas, the probability of visitation is 32 percent, compared to 26 percent in the most disadvantaged areas. Among Blacks, economic disadvantage exerts no effect on visitation, as indicated by the flat dotted line. Notably, however, the probability of visitation among Black inmates in low disadvantage areas is lower than the probability of visitation among Whites and Latinos in the high-disadvantage areas, which may stem from the possibility that Blacks experience greater overall levels of disadvantage (Alba et al. 1994).

Figure 4.

Predicted likelihood of visitation, by disadvantage, by race and ethnicity.

We turn, finally, to the question of whether the effect of distance is conditioned by the combined effects of minority status and disadvantage. Specifically, does distance yield a stronger association to reductions in visitation among minority inmates who come from disadvantaged communities? Table 4 tests this idea and finds mixed support for it. The interactions between distance and race- and ethnicity-specific disadvantage are not statistically significant among Whites and Latinos. However, a significant interaction between distance and disadvantage surfaces among Blacks. (Ancillary analyses using within-group mean centering, a different approach for obtaining estimates of cross-level interactions identified similar statistical and substantive results; Enders and Tofighi 2007.)

Table 4.

Hierarchical Logistic Regressions of Prison Visitation on Distance, Pre-prison Individual Characteristics, and County-level Disadvantage, by Race and Ethnicity, with Distance–disadvantage Interactions.

	White (n = 13,552)			Black (n = 17,418)			Latino (n = 3,145)
	b	OR	SE	b	OR	SE	b	OR	SE
Fixed effects
Intercept	0.714***	2.043	0.128	−1.029***	0.357	0.137	0.037	1.038	0.311
Individual level
Distance (/10 miles)	−0.070***	0.932	0.006	−0.074***	0.929	0.006	−0.080***	0.923	0.010
Distance²	0.001***	1.001	0.000	0.001***	1.001	0.000	0.001***	1.001	0.000
Male	−0.349***	0.705	0.065	0.302***	1.352	0.083	−0.020	0.981	0.215
Age	−0.040***	0.961	0.002	−0.028***	0.972	0.003	−0.038***	0.962	0.005
Prior commitments	−0.040***	0.961	0.002	−0.247***	0.781	0.019	−0.254***	0.776	0.069
Sentence length	−0.001**	0.999	0.000	0.000	1.000	0.000	−0.001	0.999	0.000
Prior convictions	0.009**	1.009	0.003	0.016***	1.016	0.004	0.033***	1.033	0.009
Offense—violent	−0.239***	0.787	0.065	−0.181***	0.835	0.055	−0.306*	0.736	0.122
Offense—sex	−0.446***	0.640	0.090	−0.400***	0.670	0.114	−0.566**	0.568	0.183
Offense—property	−0.395***	0.674	0.060	−0.277***	0.758	0.056	−0.362**	0.696	0.122
Offense—other	0.038	1.039	0.074	0.279***	1.322	0.069	−0.086	0.918	0.176
Time served	0.095***	1.100	0.003	0.091***	1.095	0.003	0.113***	1.120	0.007
County level and cross-level interactions
White disadvantage	−0.182*	0.834	0.077	—	—	—	—	—	—
Black disadvantage	—	—	—	0.191*	1.210	0.075	—	—	—
Latino disadvantage	—	—	—	—	—	—	−0.250	0.779	0.177
Distance × White disadvantage	0.010	1.010	0.007	—	—	—	—	—	—
Distance² × White disadvantage	0.000	1.000	0.000	—	—	—	—	—	—
Distance × Black disadvantage	—	—	—	−0.023**	0.977	0.008	—	—	—
Distance² × Black disadvantage	—	—	—	0.000**	1.000	0.000	—	—	—
Distance × Latino disadvantage	—	—	—	—	—	—	−0.008	0.992	0.016
Distance² × Latino disadvantage	—	—	—	—	—	—	0.000	1.000	0.000
Random effect
County variance	0.018		0.008	0.007		0.006	0.017		0.018

Note. Offense—drugs serves as reference category. OR = odds ratio; SE = standard error.

***p < .001.

**p < .010.

*p < 05.

Figure 5 presents the results of the interaction among Blacks graphically for ease of interpretation. Five plotlines for the predicted probabilities of visitation, by distance, are shown. Each line represents inmates from counties with a different level of disadvantage. At short distances, the distance effect is strongest among Blacks from more disadvantaged areas. For example, an increase in distance results in a greater decrease in the likelihood of visitation for Blacks from disadvantaged areas as compared to Blacks from areas that are more advantaged. However, at longer distances (e.g., beyond 350 miles), Blacks from disadvantaged areas are more rather than less likely to be visited. As we discuss in the conclusion, this pattern may result from greater knowledge among residents in more disadvantaged areas about how to negotiate overnight travel to prisons or from outreach efforts in these areas to assist impoverished family members seeking to visit loved ones in prison. It may also result from heightened efforts from spouses and partners in the most disadvantaged communities to reestablish and refocus relationships with incarcerated men (e.g., Comfort 2008; Roy and Dyson 2005).

Figure 5.

Predicted likelihood of visitation for Black inmates, by distance and disadvantage.

Discussion and Conclusions

Five main conclusions stem from this study’s findings. First, as anticipated, inmates housed farther away from their home communities were substantially less likely to be visited. This finding underscores the argument that reduced access to visitation has been an overlooked collateral consequence of incarceration. Our results accord with prior research on prison experiences and on social inequality. Both lines of work emphasize travel, and attendant logistical and fiscal challenges, as a central barrier to pragmatic goals, like employment (Western 2006; Wilson 1996), and in this instance, visitation (Bales and Mears 2008; Christian 2005; Hairston 1991).

Second, racial and ethnic disparities emerge when we examine spatial distance from prison facilities. Specifically, this study found that Blacks and Latinos on average were housed farther away from their home communities than were Whites; the disparity was substantially greater for Latinos. Descriptive analyses indicated a potential explanation—disparities in distance stem in part from the geographic distribution of minorities and of prisons, respectively. The largest capacity prison facilities were primarily located in rural regions, particularly those in the central and northern regions of Florida. By contrast, minority inmates, especially Latinos, disproportionately originated from the southern region. This geographic clustering appears to result in more distal prison placements for minorities. It is uncertain whether this finding is generalizable to other states, but it is plausible that similar patterns would emerge, particularly in large states, such as California, where regional clustering of racial and ethnic groups occurs.

Third, minority inmates were less likely to be visited than Whites. Among Latinos, this effect appears to stem from distal prison placements. Notably, Latinos who were housed close to home were more likely than any other group to be visited. Blacks were unequivocally less likely to be visited than the other groups, even after accounting for distance.

Fourth, these findings suggest that future research is required to understand racial patterning in prison visitation and, more generally, collateral consequences of incarceration. Although beyond the scope of this article, Black inmates appear to experience a range of barriers, other than spatial distance, to visitation. Even when Black inmates are housed close to home, we identified a significant disparity in visitation. Why? It is possible that even at short distances, resources and access to transportation play a role. It is also possible that other constraints exist. For example, potential visitors for poor, Black inmates might consist of individuals who cannot visit because of regulations (i.e., restricted visitation access for family members with felony records) or because they must actively seek to avoid detection. Recent work by Goffman (2009) and others (e.g., Brayne 2014) demonstrates how minority citizens from poor, high-crime neighborhoods often cannot conduct regular or necessary life activities, such as attending a funeral, going to the emergency room, or visiting a loved one in jail, because detection by law enforcement might result in arrest or a violation of supervision conditions.

The interaction analyses also indicated that, when distal prison placements were involved, Black inmates from economically disadvantaged areas were more likely to be visited than were Blacks from more advantaged areas. One explanation is that Black inmates in these areas may have more experience navigating prisons and the rules for visitation. Residents from such areas may develop a greater familiarity and experience with negotiating one- or two-day trips. Any such trips likely involve a need to carpool and arrange child care, and communities that have greater familiarity with these processes might be better equipped to enable visits to occur.

A related possibility is that familial relationships in more disadvantaged areas may be more tenuous (Wakefield and Uggen 2010; Western and Wildeman 2009). In such contexts, prison visits may provide a critical platform on which to rebuild relationships. For example, studies of the experiences of partners and spouses of male inmates from poor, minority communities suggest that partners use visits to refocus males’ attention on both them and their children to rebuild connections (Edin and Nelson 2013; Roy and Burton 2007). In short, visits may provide a critical opportunity for women and other family members to strengthen relationships and, in particular, to forge stronger ties between children and their fathers (Comfort 2008; Roy and Dyson 2005). Accordingly, family members in particular may push harder to overcome distance and other barriers to visitation.

Fifth, several directions for research emerge from this study. Future studies ideally will investigate whether distance effects operate in a similar manner in other contexts. We conducted ancillary analyses using the U.S. Department of Justice’s nationally representative 2004 Survey of Inmates in State Correctional Facilities. The results using that sample identified similar findings to those shown here—distance constitutes a significant barrier to visitation. However, the national survey provided limited ability to assess distance effects in part because it used a categorical measure of distance from home (e.g., less than 50 miles, 50–100 miles, 101–500 miles, 501–1,000 miles, 1,000 miles or more) and because it only inquired about visitation in the past month. More systematic data collection about visitation and spatial distance, and about other related dimensions that might impede visitation processes, is needed across jurisdictions to further understand these processes.

Studies are also needed that unpack additional factors associated with visitation. Distance effects, for example, may be less relevant than access to affordable public transportation. By extension, future research should consider how other areas of scholarship might inform efforts to understand patterning in visitation access. Research on health and services utilization (Andersen 1995), for example, may be helpful by emphasizing the importance of looking beyond pragmatic, structural barriers, and considering social and cultural mechanisms (e.g., community and family ties) that may influence visitation patterns. In this same vein, studies are needed that identify how exactly community contexts and social networks contribute to visitation. For example, community organizations and nonprofit groups may help potential visitors overcome distance and other barriers and may be more readily available in socially disadvantaged communities. Accounting for these types of assistance programs in statistical models, and examining their effects, can shed further light on the mechanisms that contribute to social disparities in visitation identified here.

Not least, there is, more broadly, a need for research on other incarceration experiences that may affect in-prison and post-release behavior (Mears 2012; Nagin et al. 2009). For example, few studies exist that identify which prison experiences increase or relieve strain (e.g., Blevins et al. 2011), strengthen or weaken social bonds (e.g., Hairston 1991), or reduce or increase social capital (e.g., Wolff and Draine 2004). Investigating inmate experiences in prison will be critical to developing a better understanding of the impacts of punishment and how punishment theory and effectiveness might be improved.

Policy implications from one study should be made with caution. Here, one tentative implication that warrants mention is the potential need for prison systems to place inmates close to their home communities. Doing so may be difficult, given that inmates frequently are located hundreds of miles from their homes (e.g., Coughenour 1995; Mumola 2000; Osborne Association 2012). Even so, as this study found, many inmates may live sufficiently far away from their home communities to require overnight stays for visits. Such placements create barriers not only to visitation but also to reentry preparation that can effectively link inmates with services to local community agencies (Petersilia 2005; Travis 2005).

Footnotes

Acknowledgment

We thank Emily Leventhal for assistance provided during the development of this article and the editor and anonymous reviewers for their helpful feedback and suggestions. We also thank the Florida Department of Corrections for permission to use their data.

Authors’ Note

Earlier versions of this article were presented at the 2013 Annual Meeting of the American Society of Criminology and the 2014 Annual Meeting of the Academy of Criminal Justice Sciences. The views expressed here are those of the authors and do not reflect those of the Department of Corrections.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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