PRINT VERSION CITATION: Cochran, Joshua C., Daniel P. Mears, and William D. Bales.
2017. “Who Gets Visited in Prison? Individual- and Community-Level Disparities in Inmate
Visitation Experiences.” Crime and Delinquency 63(5):545-568.
Who Gets Visited in Prison?*
Joshua C. Cochran, Daniel P. Mears, and William D. Bales
*Direct correspondence to Joshua C. Cochran, Ph.D., University of South Florida, Department of
Joshua C. Cochran, Ph.D., is an Assistant Professor in the Department of Criminology at the
University of South Florida, 4202 East Fowler Avenue, Tampa, FL 33620-7200, email
(email@example.com), phone (813-974-9708). His research interests include criminological
theory, juvenile court sentencing, imprisonment, and prisoner reentry. He has published in
Criminology, Journal of Research in Crime and Delinquency, Journal of Quantitative
Criminology, and other crime and justice journals.
Daniel P. Mears, Ph.D., is the Mark C. Stafford Professor of Criminology at Florida State
University’s College of Criminology and Criminal Justice, 634 West Call Street, Tallahassee, FL
32306-1127, phone (850-644-7376), fax (850-644-9614), e-mail (firstname.lastname@example.org). He
conducts basic and applied research, and his work has appeared in leading crime and policy
journals and a book, American Criminal Justice Policy (Cambridge University Press), which
received the Academy of Criminal Justice Sciences Outstanding Book Award.
William D. Bales, Ph.D., is a Professor at Florida State University’s College of Criminology
and Criminal Justice, 634 West Call Street, Tallahassee, FL 32306-1127, phone (850-644-7113),
fax (850-644-9614), e-mail (email@example.com). He focuses on a range of crime and policy topics,
including the effectiveness of electronic monitoring and tests of labeling theory. He has
published in Criminology, Criminology and Public Policy, and other crime and policy journals.
Who Gets Visited in Prison?
Scholarship has shown that visitation helps individuals to maintain social ties during
imprisonment, which, in turn, can improve inmate behavior and reduce recidivism. Not being
visited can result in collateral consequences and inequality in punishment. Few studies,
however, have explored the factors associated with visitation. This study uses data on Florida
inmates to identify individual- and community-level factors that may affect visitation.
Consistent with expectations from derived from prior theory and research, the study finds that
inmates who are older, Black, and who have been incarcerated more frequently, experience less
visitation. In addition, inmates who come from areas with higher incarceration rates and higher
levels of social altruism experience more visits. Unexpectedly, however, sentence length and
economic disadvantage are not associated with visitation. Implications of these findings are
Key words: visitation, prison experiences, social ties, social isolation, inequality
A growing body of scholarship underscores the importance of social ties for improving in-
prison and reentry outcomes (La Vigne et al. 2004; Maruna and Immarigeon 2004; Jiang and
Winfree 2006; Cobbina et al. 2012; Listwan et al. 2013). One avenue of research that has
garnered particular attention is inmate visitation (see, e.g., Hairston 1991; Bales and Mears 2008;
Monahan et al. 2011; Duwe and Clark 2013; Siennick et al. 2013). Research has found that
inmates with social ties to family more likely maintain conventional social roles and cope better
with strain and social isolation and reentry back into society (Lembo 1969; Ellis et al. 1974;
Adams 1992; Gordon and McConnell 1999; Wolff and Draine 2004; Christian 2005; Jiang and
Winfree 2006; Lahm 2008; Blevins et al. 2010; Cochran and Mears 2013; Duwe and Clark
Despite scholarly attention to visitation and the potential benefits to correctional systems of
social support for inmates and ex-prisoners, little is known about the factors that contribute to
visitation. This research gap is surprising for several reasons. Visitation could be used to
improve prediction of which inmates most likely will engage in misconduct or recidivate
(Bushway and Apel 2012; Cochran and Mears 2013). Just as importantly, increased visitation
constitutes a central strategy through which corrections systems might improve social order in
prisons and post-release outcomes (Jackson et al. 1997; Christian et al. 2006; see also Schafer
1978). At the same time, disparities in visitation constitute a form of potentially unequal
punishment, a collateral consequence (Travis 2005), concentrated more among some groups,
such as minorities, than others (Western 2006; Bales and Mears 2008).
The goal of this paper, then, is to examine individual- and community-level factors that may
be associated with prison visitation. In so doing, the paper responds to calls from scholars (e.g.,
Nagin et al. 2009; Mears 2012; Visher and O’Connell 2012; Duwe and Clark 2013) to describe
and understand better the nature of in-prison experiences and their salience for prison order and
reentry. The paper begins by describing prior research on prison visitation and the implications
of visitation for inmate and ex-prisoner behavior. We then discuss characteristics of inmates,
and of the community contexts from which they come, that may influence visitation. Using data
from a population cohort of all inmates admitted to and released from Florida prisons between
November 2000 and April 2002, we presents multi-level negative binomial analyses that
estimate the effects of individual- and community-level factors on visitation. We conclude by
discussing research and policy implications of the study.
THE THEORY AND EFFECTS OF INMATE VISITATION
The expansion of the correctional system in recent decades has led to growing concerns
about the effects of incarceration and the implications of prison experiences for affecting in-
prison and reentry outcomes (Adams 1992; Bottoms 1999; Liebling 1999; Nagin et al. 2009;
Cullen et al. 2011). Prison experiences are heterogeneous. The dimensions along which they
can vary include educational and vocational programming and drug and mental health treatment,
victimization or gang activities, exposure to different inmate cultures or administrative
approaches, and more (see, generally, Sykes 1958; Bonta and Gendreau 1990; Gendreau and
Keyes 2001; Blevins et al. 2010; Tasca et al. 2010; Mears 2012; Listwan et al. 2013). Recent
reviews suggest that little is known about how such experiences affect inmate behavior and post-
release outcomes, such as recidivism (Nagin et al. 2009; Jonson 2011; Mears 2012). They
suggest, too, that little is known about the experiences themselves. During an era in which mass
incarceration has led to increased attention to recidivism and efforts to reduce it, this research
gap stands out, given the potential for variation in inmate experiences to affect misconduct and
Prior scholarship suggests that a critical experience for inmates involves access to social ties
during incarceration (e.g., Adams and Fischer 1976; Hairston 1991; Liebling 1999). Prison
visitation represents, by and large, the only opportunity inmates have for direct contact with
outside social networks, and has led scholars to emphasize its benefits for improving behavior
(Ohlin 1951; Glaser 1954; Holt and Miller 1972; Hairston 1988). Questions remain about the
effects of visitation and how the effects arise. In general, however, extant research has
consistently found that visitation is associated with improved prison behavior (see, e.g., Goetting
and Howsen 1986; Clark 2001; Hensley et al. 2002; Lahm 2008; Cochran 2012; see, however,
Jiang and Winfree 2006; Siennick et al. 2013) and reduced recidivism (e.g., Bales and Mears
2008; Monahan et al. 2011; Mears et al. 2012; Duwe and Clark 2013).
Scholars have identified a diverse array of avenues, or theoretical pathways, through which
visitation may achieve various outcomes. Research highlights that inmates themselves view
maintenance of social ties as especially important (Fishman 1990; Adams 1992; Comfort 2003,
2008; Ross and Richards 2009; George 2010). Visitation can help reduce strain and help inmates
cope with social isolation in prosocial ways, thereby reducing prison disorder (e.g., Adams 1992;
Bottoms 1999; Blevins et al. 2010; Morris et al. 2012). Visitation also can help inmates maintain
social bonds, which in turn can result in informal controls that reduce the likelihood of prison
misconduct and recidivism (e.g., Hirschi 1969; Holt and Miller 1972; Hairston 1991; Gordon and
McConnell 1999; Trulson et al. 2011; Cochran et al. 2013). Inmates who are visited, and who
take part in other types of in-prison programs and privileges, may be more likely to view prison
authority as legitimate (see, e.g., Bottoms 1999; Reisig and Mesko 2009). Not least, visited
prisoners are better able to access social resources and capital, which can provide practical
benefits upon release (e.g., Ekland-Olson et al. 1983; Petersilia 2003; La Vigne et al. 2005;
Makarios et al. 2010; Berg and Huebner 2011; Cobbina et al. 2012).
THE SALIENCE OF IDENTIFYING WHO GETS VISITED
In short, theory and empirical research suggest that visitation, and social ties more broadly,
can improve inmate behavior and reentry outcomes. This body of work underscores the need to
investigate a more fundamental question: Who gets visited in prison? Surprisingly, extant
research provides few answers to this question (Jackson et al. 1997; Cochran and Mears 2013).
It thus remains unclear, for example, how age, gender, race, ethnicity, the characteristics of the
areas from which inmates come, and other such factors influence visitation.
Greater attention to understanding who gets visited is warranted for several reasons. First, to
the extent different types of inmates are less likely to be visited, questions of fairness and equity
emerge. Visitation may have benefits and it is, with some exception, a right granted to offenders
(Overton v. Bazzetta 2003; see Kent 1975; Hardwick 1985; Schafer 1978). Conversely, limited
visitation can constitute a form of punishment, a collateral consequence (Travis 2005). Evidence
of differential visitation may indicate structural inequalities or practical constraints that, however
justified, may disproportionately favor or burden some inmates. Although correctional systems
cannot control inmate social networks outside the prison walls, they can adopt policies that
promote or inhibit visitation and social contact more broadly (Bales and Mears 2008).
Second, as emphasized above, a lack of visitation constitutes an additional punishment on
some inmates that may constitute a form of unequal treatment and that may perpetuate social
disadvantage (e.g., Hagan and Dinovitzer 1999; Mauer and Chesney-Lind 2002; Travis 2005;
Beckett and Murakawa 2012; Cochran and Mears 2013). Collateral consequences constitute
adverse events or experiences that stem from a sanction. Inmates report that the severing of ties
to family and friends constitutes one of the most important fears that they have about
incarceration (Adams 1992). Viewed in this light, impediments to visitation, especially if more
pronounced for some groups, create greater punishment for them. For example, to the extent that
such punishment is patterned along social and demographic lines, it raises questions about the
social inequality in punishment in America (Western 2006).
Third, examining the factors associated with visitation can inform studied aimed at
understanding how and why visitation effects occur. For example, if racial or ethnic differences
in visitation effects exist, these differences may result not from a causal effect of race or
ethnicity, or from any attribute of the system itself, but rather from differences in social capital
and resources associated with race, ethnicity, or both (Mears et al. 2012). Identifying dimensions
along which visitation varies thus provides a foundation both for assessing the effects of
visitation and for examining how such effect arise.
Fourth, and not least, understanding the factors that influence visitation may enable prison
administrators to take policy steps to increase visitation and to reduce disparities in visitation.
Such a possibility carries with it the attendant risk of worsening outcomes if, in fact, visitation
produces harmful effects (e.g., Siennick et al. 2013). Visitation from criminal associates, for
example, is not on the face of it likely to improve outcomes and may worsen them (Bales and
Mears 2008). Even so, the bulk of research and theory to date indicates that visitation can have
beneficial effects (Monahan et al. 2011; Mears et al. 2012; Cochran 2014; Duwe and Clark 2013;
Visher 2013). Accordingly, information about who gets visited provides a first step in
highlighting factors related to reduced visitation. These factors in turn constitute starting points
for identifying methods for corrections systems to increase visitation to improve in-prison and
post-release outcomes and reduce disparities in the collateral consequences of incarceration.
WHO GETS VISITED IN PRISON?
What factors then are associated with visitation? Drawing on prior theory and research, we
examine characteristics of inmates and their communities that research implicates as potential
determinants of visitation. We begin by examining individual characteristics, including inmate
demographics, prior record, and conviction offense. Then, building on a growing body of
literature that highlights the importance of contextual factors on offender experiences and
behavior (e.g., Travis and Visher 2003; Kubrin and Stewart 2006; Mears et al. 2008; Hipp et al.
2010; Wang et al. 2010), we investigate the possibility that characteristics of the counties
inmates come from, such as economic disadvantage, community members’ contact with the
prison system, and social altruism, may be associated with prison visitation.
Gender. Female inmates are likely to have stronger, more stable social networks (Moore
1990; Cobbina et al. 2012). Females are also more likely to take a more substantial role in the
care taking of children than are males and to put more effort into maintaining ties with family
and friends (Uggen and Kruttschnitt 1998). Research suggests that familial ties exert stronger
effects on behavior than do friends or peers and that females have stronger attachments to the
former than to the latter, when compared to males (Cobbina et al. 2012). Also, the friendships
that females do develop typically are more intimate and affectionate (Giordano, Cernkovich, and
Pugh 1986; Steffensmeier and Allan 1996). This work suggests that females will experience
more contact and be visited more often than males during incarceration (see also Datesman and
Cales 1983; Visher and Courtney 2006).
Age. Prior research suggests that younger inmates may experience more visitation than older
inmates. Although young adulthood is the period during which offending peaks and social bonds
may begin to weaken (see, generally Gibson and Krohn 2013), younger offenders are more likely
than older offenders to still be involved with their family, including parents, guardians, and
siblings. Over time, older inmates are more likely to have drifted away from tight-knit family
and peer groups (Rose and Clear 2003; Uggen and Wakefield 2005). Furthermore, younger
inmates, because of their age, may be perceived by family and friends as less culpable than their
older counterparts (Massoglia and Uggen 2010). Thus, incarceration itself may sever social ties
for older inmates more so than younger inmates, leading to decreased visitation for older groups.
Not least, younger inmates may be perceived as more vulnerable to the harshness of prison life
and so create a greater urgency among family and friends to visit.
Race and ethnicity. Minority inmates typically have fewer years of formal education,
experience greater socioeconomic disadvantage, and have had more frequent contact with the
criminal justice system (Wacquant 2001; Western 2006; Wakefield and Uggen 2010; Pettit
2012). Their potential visitors—their family and community members—are likely to share many
of these characteristics. Thus, minority groups may experience less visitation because their
outside social ties have fewer social and economic resources, experience greater difficulty in
obtaining transportation to prisons, have difficulty paying fees associated with visitation, and,
more generally, may face more challenges in overcoming the many barriers to visitation
identified in prior research (see, e.g., Hardwick 1985; Casey-Acevedo and Bakken 2002;
Comfort 2003; Christian 2005; Hoffman et al. 2005; Christian et al. 2006).
Prior scholarship implicates race and ethnicity in other ways. Adams (1992) argues, for
instance, that Latino inmates have greater levels of social support because of the tight-knit family
structures inherent in Latino communities; this difference, in turn, might result in more visitation
among Latinos. Also, minority inmates typically will be more likely than Whites to come from
community contexts where incarceration is a more familiar phenomenon, and thus where a
greater understanding exists about how to negotiate the prison experience (e.g., Wacquant 2001).
Prior record and offense seriousness. Scholarship indicates that prior record and offense
seriousness are associated with less visitation. Inmates who have been convicted and imprisoned
more frequently, and who have committed more serious offenses, may be less likely to
experience visitation. Research suggests that serious or chronic offenders have lower levels of
social support and fewer social resources than first-time and less serious offenders (Rose and
Clear 2003; Gibson and Krohn 2013). As individuals engage in more offending, their social
relationships may become strained (Rose and Clear 2003; Roberts 2004). Visitors who
previously were willing to visit may grow weary of investing the effort to visit as individuals
accumulate more convictions and experience multiple stints of incarceration (e.g., Christian
2005; Christian et al. 2006). The type of offense, too, can be consequential. For example,
violent and sex offenders may experience less visitation than inmates who commit property or
drug offenses or who are incarcerated for violations of probation and parole. Family or friends
may view such crimes as more egregious or as greater violations and thus be less forgiving and
less willing to continue to invest time, money, and resources on individuals who commit them.
Economic disadvantage. As discussed above, inmates who come from areas with heightened
levels of economic disadvantage may experience less visitation. Family, friends, and community
members from these areas—an inmate’s pool of potential visitors—are more likely to be
unemployed or to have low-paying jobs, and, because of a range of practical constraints, will
have diminished abilities to overcome challenges related to visitation. Although potential
visitors from such areas might be similarly, if not more, willing to visit incarcerated offenders,
individuals from them typically will have fewer resources to allow them to take time off from
work, to travel or pay for transportation to a prison, to find childcare, and to pay fees (e.g.,
background check, parking) related to visitation (e.g., Christian 2005; Tewksbury and
Prison admission rates. Two theoretical arguments suggest that areas with higher rates of
incarceration would give rise to more visitation. Similar to arguments about the potential effects
of race, citizens in these areas might be more familiar with incarceration and have more
experience with the complexities involved with managing imprisonment and navigating the
administrative systems surrounding inmate visitation. The end result would be more visits. It is
possible, for example, that in these areas informal infrastructures exist that make it easier to visit;
residents may be more likely to carpool together or provide childcare to assist other community
members in visiting family in prison (see, generally, Rose and Clear 2003; Cammett et al. 2006).
A different line of reasoning leads to a similar prediction about the effects of aggregate
incarceration rates on visitation. Studies suggest that groups that perceive that they are unfairly
targeted by the criminal justice system, such as when citizens live in areas where incarceration
occurs frequently, exhibit greater skepticism about the behavior and legitimacy of criminal
justice actors (Tyler 1990; Weitzer and Tuch 2006). Similarly, qualitative accounts suggest that,
under some circumstances, visitors are skeptical of the treatment friends and loved ones receive
while incarcerated (Christian 2005). Thus, family and community members who come from
areas where criminal justice contact is more frequent may have a greater willingness to visit
inmates from those areas if they feel that it helps to increase prison accountability.
Social altruism. Not least, inmates who come from areas where levels of social cohesion or
social altruism are higher may also experience more visitation (see, generally, Chamlin and
Cochran 1997; Putnam 2000; Rosenfeld et al. 2001). Recent scholarship has highlighted
significant effects of group-level social capital, social welfare, and social support on released
prisoners’ ability to reintegrate into society upon release (Rose and Clear 2003; Holtfreter et al.
2004; Hipp et al. 2010; Orrick et al 2011). The bulk of these studies suggest that inmates who
return to areas with higher levels of social capital are better off during prisoner reentry. What
about during incarceration? It seems reasonable to expect that, drawing on this body of work,
community social support or social cohesion can impact offenders, perhaps via visitation, prior
to release (e.g., Wolff and Draine 2004). Communities with more social capital have increased
social integration and larger amounts of collective outreach (e.g., Coleman 1990; Putnam 2000;
Rosenfeld et al. 2001). Visiting offenders in prison requires a substantial amount of effort, but
communities with heightened levels of social altruism may contain larger pools of family and
community members motivated to help offenders in prison and to overcome these obstacles.
DATA AND METHODS
This paper uses data from an admissions cohort of all felony inmates admitted into and
released from Florida prisons between November 2000 and April 2002 (n = 17,921). The data
are provided by the Florida Department of Corrections (FLDOC) and contain detailed measures
including demographic, offense, prior record, sentence length, and time served measures. Only
inmates who served at least 2 months in prison are included to ensure that visitation was possible
and to address the fact that initial screening facilities are not where inmates spend the duration of
their term of incarceration. Ancillary analyses that included all inmates, regardless of time
served, revealed substantively similar findings and are available upon request. To test the extent
to which county-context measures predict visitation, individual-level data were linked to county-
level information based on the county in which individuals committed their offense. The
specific measures included in the analyses are described in more detail below (see table 1).
Insert table 1 about here
The dependent variable used here is a count measure of inmate visitation. Visitation records
for inmates are electronically recorded by prison officers into the FLDOC Offender Based
Information System (OBIS). For the analyses, visitation counts were truncated at 35 to reduce
skew in the measure (99 percent of the sample had 35 or fewer visits).
Demographic factors in the OBIS system include inmates’ age (continuous), race and
ethnicity (Black non- Latino, White non- Latino, or Latino), and sex (male = 1, female = 0).
Each of these is included in the analyses as independent variables. The analyses also include two
measures of prior criminal history: the prior number of felony convictions (count) and the prior
number of prison commitments (count). Inmates are designated as having committed one of five
different primary offense types. These are included as dichotomous measures and can be drug,
violent, sex, property, or other. Continuous measures of inmates’ sentence length (in months)
and time served (in months) are also included as independent variables. Time served is included
here to control for differential opportunities to be visited over time.
The analyses also include three county-level independent variables. First, the analyses
include a measure of county-level economic disadvantage. This measure is consistent with
disadvantage and deprivation indices used previously by researchers (e.g., Land et al. 1990) and
in prior studies that have analyzed Florida county data specifically (e.g., Wang et al. 2010). The
index includes four measures based on 2000 U.S. Census data: percent female-headed
households, percent under the poverty line, unemployment rate, and percent households on
public assistance. Second, to test the effects of county-level contact with the prison system on
visitation, the analyses include the rate of prison admissions per 1,000 for each county for the
year 2000. This measure is based on data provided by the FLDOC that provides counts of all
new admissions to prison from each county. These counts were then divided by the population
for each county based on the 2000 U.S. Census. Third, to test the effects of social outreach or
social altruism on visitation, the analyses include a measure of county-level charitable revenue,
measured in units of $10,000 per household. This measure was obtained from the Urban
Institute’s National Center for Charitable Statistics (nccsdataweb.urban.org) and is for the year
2000. Scholars have identified charities and charitable donations as measures of altruism, social
capital, and social support (Chamlin and Cochran 1997; Orrick et al. 2011; Sampson 2013).
The dependent variable in the analyses is a count measure of visitation, and thus linear
models are not appropriate. In addition, a modeling strategy is required that can account for
nesting of cases within counties. To account for the count-based nature of the outcome and the
hierarchical structure of the data, multilevel Poisson models were analyzed using Stata’s
xtmepoisson procedure (see Rabe-Hesketh and Skondral 2008).
Similar to previous studies employing multilevel regression, the analyses followed a two-step
process. Step one involved assessing the extent to which inmate visitation varied at the county
level. If there is significant variation across level 2 units, this variation may be attributed to two
factors: compositional characteristics of the inmates within those counties and county-level
attributes. To assess variability at the county level in prison visitation, a fully unconditional
multilevel Poisson model was analyzed. The county-level random effects variance component
(0.147) in this model was statistically significant at the p=.001 level, suggesting significant
variance in counts of inmate visitation across counties. Counties with fewer than 15 inmates
were excluded from the analyses, which removed 104 inmates. (Ancillary analyses with the full
sample revealed similar results to those shown in the tables and are available upon request.)
One problem with using the Poisson distribution for these analyses is that the number of zero
counts in the dependent variable leads to overdispersion. For example, the variance in the
outcome (33.53) is more than 10 times greater than the mean (2.13). This overdispersion was
confirmed further by two goodness-of-fit tests: a deviance test and a Pearson test. In both
instances, the tests were statistically significant and suggested that the Poisson model was
inappropriate. Therefore, the multivariate models described below are based on multilevel
random effects negative binomial regression models, using Stata’s xtnbreg command, which can
account both for overdispersion in the count outcome and for the clustering of inmates within
level 2 units (see, e.g., Osgood 2000; Parker 2004; Stucky et al. 2012). Ancillary analyses
showed that the results for the negative binomial and Poisson models were substantively similar.
Table 1 provides descriptive information about the inmate cohort and covariate measures.
Inspection of table 1 highlights that, on average, inmates received 2.13 visits over the course of
their incarceration period. Inmates typically were male (90%) and had an average age of 32.
Forty-two percent were White, 50% were Black, and 8% were Latino. A significant strength of
the analyses is that, in contrast to prior work, a sufficiently large number of females and Latinos
can be included to examine gender and racial/ethnic variation in visitation.
The analyses also consider the effects of prior record, sentencing, and offense information.
On average, inmates in the cohort served about 1 prior prison commitment (0.87), averaged 6
prior convictions (5.90), and were sentenced to 23 months of incarceration (22.81). The most
common offense type was a drug crime (34%), followed by property (32%), violent (19%), other
(13%), and sex (3%) crimes. Inmates, on average, served 12 months in prison (12.27).
An additional strength of the study is the inclusion of information about the characteristics of
the counties from which inmates come. The first county-level variable is a standardized index of
economic disadvantage. The second county measure is the prison admissions rate per 1,000
citizens in a county; the average prison admission rate is approximately 2 per 1,000 citizens
(1.98), with a range of 0.48 to 4.30. Last, county-level charitable revenue averages about $5,000
per household in charitable giving and values range from $100 to $27,000 per household.
Turning to the multivariate results in table 2, we investigate the effects of the independent
variables on the likelihood of visitation. Table 2 presents the results of random effects,
multilevel negative binomial regression models. Model 1 includes the individual-level variables
only; model 2 then includes the county-level attributes.
Insert table 2 about here
Inspection of model 1 shows that several factors are statistically significant and related to
visitation. Beginning first with the demographic measures, we can see that males experience
fewer visits than females (b = -.125) and that older offenders experience fewer visits than
younger offenders (b = -0.037). In addition, Blacks receive fewer visits (b = -.712) and Latinos
receive fewer visits (b = -.120), respectively, as compared to Whites.
Inmates with more prison commitments also experience significantly less visitation (b = -
.183). Somewhat surprisingly, there is a positive and statistically significant effect of prior
convictions on visitation. Although this effect is small (b = .014), it runs counter to arguments
that would suggest that chronic offenders would receive fewer visits. However, as expected,
inmates who committed more serious offenses (e.g., violent and sex offenses) experienced
significantly less visitation. Compared to drug offenders, violent (b = -.209), sex (b = -.323), and
property (b = -.322) offenders each experienced significantly fewer visits. “Other” offenders (b
= .086) experienced more visitation, but this effect did not reach statistical significance. Finally,
sentence length had no statistically significant effect on visitation, but time served did; each
additional month of time served was associated with a .077 increase in the log count of visits.
Model 2 includes the same individual-level variables as model 1, but incorporates county-
level measures as well and serves to investigate whether conditions in the areas from which
inmates come may influence visitation. Notably, the individual-level effects are nearly identical
between model 1 and 2, even after the addition of county-characteristics, indicating that area-
level effects operate largely independently of individual-level effects. Two characteristics exert
statistically significant effects on county-level variation in visitation. Inmates from counties with
higher rates of prison admissions or with higher levels of charitable giving were visited more
frequently (b = .049 and b = .143, respectively).
Insert figure 1 about here
To present the effects identified in table 2 in a more intuitive manner, figure 1 provides
predicted visitation counts for individuals with different characteristics. The predicted counts
were generated using model 2 coefficients, holding all other covariates at their means.
Inspection of figure 1 highlights that age and race and ethnicity have substantial effects on
visitation. In this study, a 20-year old inmate on average received approximately 2.6 visits; by
contrast, the typical 50-year old inmate experienced less than one visit. White inmates were
estimated to receive approximately .25 visits more than Latino inmates, and approximately 1.25
more visits than Black inmates. We can see also that substantively large differences exist across
prior commitments and offense type. Specifically, an inmate incarcerated for the first time is
estimated to receive nearly 2 visits compared to a little over 1 visit for someone who is
incarcerated a third time. Drug and other offenders are estimated to receive about .5 more visits
as compared to violent, sex, and property offenders.
Similar to prior studies, the gender differences appear to be small (see, e.g., Mumola 2000).
There are non-trivial differences, however, with respect to county-level prison admission rates
and county-level charitable giving. The high and low values for prison admission rates and
charitable revenue are based on the predicted counts of visitation for inmates from counties in
the top and bottom deciles for those two measures, respectively. Inmates from counties in the
top decile of these two variables receive about .20 to .25 more visits than inmates from the low
decile of these two variables. The magnitude of this effect appears small. However, the effect
applies to all inmates who come from the top decile and bottom decile counties, respectively.
These analyses underscore the notion that males, older inmates, and more experienced
offenders have fewer social ties, or less access to social ties, while incarcerated (Uggen and
Kruttschnitt 1998; Massoglia and Uggen 2010; Cobbina et al. 2012). They also lend support to
the idea that more serious offenders are likely to have weaker social networks, but also, that
imprisonment is likely detrimental to social ties (Sampson and Laub 1993; Rose and Clear 2003;
Roberts 2004; Gibson and Krohn 2013). Not least, the findings highlight the possibility that
inmates’ former social contexts may exert significant influences on their in-prison experiences.
The findings above were robust across a range of alternate specifications. For example, the
multivariate analyses shown here used grand-mean centered level 1 variables. This approach
allows for more accurate effect estimates for the effects of level 2 (county) characteristics. The
alternative is within-group centering, which provides more accurate estimation of coefficients at
level 1 (see Enders and Tofighi 2007). Analyses using within-group centering revealed
substantively identical findings for level 1 estimates, suggesting that the estimated effects of the
covariates on visitation are robust across modeling approaches.
DISCUSSION AND CONCLUSION
The expansion of the correctional system over the past three decades has led to scholarship
aimed at understanding the effects of incarceration. It also has led to the creation of a body of
work aimed at understanding the implications of social support for offenders (e.g., Berg and
Huebner 2011; Cobbina et al. 2012; Orrick et al. 2012; Steiner et al. 2013). This work has
identified visitation as an experience that can improve inmate behavior, reduce recidivism, and
contribute to successful reentry (e.g., Monahan et al. 2011; Duwe and Clark 2013). At the same
time, there remains almost no research that identifies who gets visited (Jackson et al. 1997). This
gap is problematic because a lack of visitation can be viewed as a collateral consequence—a
form of additional punishment—that is experienced more acutely by some groups, such as racial
and ethnic minorities, than others. It is problematic, too, because efforts to improve risk
prediction, inmate behavior, and reentry success may be improved by efforts to increase
visitation and, more broadly, to create stronger social networks for inmates and ex-prisoners
(Petersilia 2003; Travis 2005). Any such improvements, however, depend heavily on an ability
to understand better the factors associated with inmate visitation.
The goal of this study was to address this research gap—and in turn inform scholarship and
policy efforts aimed at understanding and improving inmate behavior and public safety—by
identifying whether specific social and demographic groups, as well as inmates from different
social contexts, are more likely or less likely to be visited. Three sets of findings emerged from
the study. First, the analyses show that some groups in fact receive more visits and so have
greater access to outside social ties during incarceration. Specifically, inmates who are young,
female, White, or Latino experience the greatest amounts of visitation. Second, individuals with
more extensive prior records, including those convicted of more serious crimes or incarcerated
previously, experience less visitation. Third, social context affects visitation. Specifically, we
identified a positive association between county-level prison admission rates and charitable
giving, on the one hand, and visitation, on the other hand.
These findings provide important insights into the prison experience. We begin first with the
observation that inmate groups vary in their likelihood of visitation. In turn, that means that they
vary in the collateral consequences of incarceration. They will be more likely to fare poorly
during and after incarceration. Many studies already have documented that a lack of visitation,
and, more generally, limited social support and resources, contributes to inmate maladjustment,
misconduct, and poor reentry outcomes, including increased recidivism (Hairston 1991; Adams
1992; Wolff and Draine 2004; Bales and Mears 2008; Blevins et al. 2010; Berg and Huebner
2011; Cochran 2012; Visher and O’Connell 2012; Cochran et al. 2013). If punishment policies
are to effectively enhance public safety, addressing such variation constitutes an important issue
to address. Failure to improve inmate visitation and social support amounts to a “get tough”
punishment approach that may increase rather than decrease recidivism (Nagin et al. 2009).
Second, the patterns identified in this study accord with prior work that has identified
disparities associated with mass incarceration and the “punitive turn” to be more concentrated
among minorities (Wacquant 2001; Western 2006; Wakefield and Uggen 2010). Disparities in
visitation, as with access to public housing and with the right to vote, raise concerns about equity
in American justice. In addition, they point to the potential for “invisible punishments”
associated with mass incarceration to arise that can amplify existing inequalities. Minority
inmates, for example, typically come from socially disadvantaged areas and may experience less
visitation, with potential adverse effects for the inmates’ families and children. The adverse
effects may continue upon release through an increase in recidivism and a failure to obtain
housing, employment, or mental health services. In short, the disproportionate impact of mass
incarceration policies can be seen not only in the large numbers of minorities sent to prison and
in such collateral consequences as impeded access to housing and the right to vote, it also can be
seen in a much more basic way—the ability of inmates to maintain social ties to their families
and communities, and, at the same time, the ability of these families and communities to
minimize harms associated with mass incarceration.
The potential for impeded visitation to adversely affect prison and reentry outcomes and to
amplify social inequality underscores the need for policies that expand inmate access to social
networks during incarceration. What can be done? Corrections systems should focus on
identifying and removing existing barriers that reduce visitation opportunities, especially those
that are responsible for creating unequal visitation. Such efforts hold the potential for improving
prison order and public safety and for reducing inequalities that can emerge during or as a result
of the prison experience—two critical goals for any prison system.
Steps for removing these barriers or for reducing their influence begin with the process of
identifying them. Distance alone constitutes one of the more likely barriers. On average,
inmates are housed more than 100 miles away from home (Mumola 2000). Many potential
visitors must rely on public transportation for travel (Tewksbury and DeMichele 2005). This
constraint, coupled with limited finances, reduces the likelihood of visitation. In addition,
potential visitors, especially those who work low-wage jobs and have children, frequently cannot
afford to take time off from work or will not be permitted to do so or cannot afford childcare that
would enable visits (Christian 2005; Christian et al. 2006).
What can be done? Corrections systems undertake can seek to house inmates closer to their
home communities. Administrators can also consider efforts to improve public transportation to
and from facilities. These strategies may be especially effective in larger states where prisons
are scattered across rural regions, far away from the metropolitan areas where most inmates
originate and where their pools of potential visitors likely reside. An additional strategy for
improving visitation is to make facilities more child-friendly through more flexible visitation
hours, provision of childcare, and creation of settings that include games and books. Not least,
correctional systems should consider outreach and educational efforts for inmates’ families
before and during a term of incarceration. These efforts should focus on explaining to the
families and other potential visitors about the importance of social support for inmates and how
to negotiate rules for and logistical challenges associated with visitation.
Alongside of such efforts is the need for substantially more empirical research on the factors
associated with inmate visitation and, more broadly, social support during and after incarceration
(Cochran and Mears 2013; Listwan et al. 2013). This study has identified the particular
importance of focusing not only on individual-level characteristics but also on characteristics of
the communities from which inmates come. Scholarship has identified many barriers to
visitation and social support (e.g., Tewksbury and DeMichele 2005; Bales and Mears 2008).
States should seek to document empirically facility rates of visitation and the barriers specific to
each prison. Such information in turn can be used to determine what steps should be taken to
increase visitation and social supports for inmates. Not least, it can be used to assess over time
equity in the prison experiences of different inmate populations and the extent to which visitation
and social support improve inmate behavior and reentry success.
Adams, Kenneth. 1992. Adjusting to Prison Life. Crime and Justice 16:275-359.
Adams, Don and Joel Fischer. 1976. The Effects of Prison Residents’ Community Contacts on
Recidivism Rates. Corrective and Social Psychiatry and Journal of Behavioral Technology,
Methods, and Therapy 22:21-27.
Bales, William D. and Daniel P. Mears. 2008. Inmate Social Ties and the Transition to Society:
Does Visitation Reduce Recidivism? Journal of Research in Crime and Delinquency
Beckett, Katherine and Naomi Murakawa. 2012. Mapping the Shadow Carceral State: Toward
an Institutionally Capacious Approach to Punishment. Theoretical Criminology 16:221-244.
Berg, Mark T. and Beth M. Huebner. 2011. Reentry and the Ties that Bind: An Examination of
Social Ties, Employment, and Recidivism. Justice Quarterly 28:382-410.
Blevins, Kristie R., Shelley Johnson Listwan, Francis T. Cullen, and Cheryl Lero Jonson. 2010.
A General Strain Theory of Prison Violence and Misconduct: An Integrated Model of
Inmate Behavior. Journal of Contemporary Criminal Justice 26:148-166.
Bonta, James and Paul Gendreau. 1990. Reexamining the Cruel and Unusual Punishment of
Prison Life. Law and Human Behavior 14:347-372.
Bottoms, Anthony E. 1999. Interpersonal Violence and Social Order in Prisons. Crime and
Justice 26: 205-281.
Bushway, Shawn D. and Robert Apel. 2012. A Signaling Perspective on Employment-Based
Reentry Programming. Criminology and Public Policy 11:21-50.
Cammett, Ann, Johnna Christian, Nancy Fisherman, and Lori Scott-Pickens. 2006. Bringing
Families In: Recommendations of the Incarceration, Reentry and Family Roundtables.
Scholarly Works. Paper 570.
Casey-Acevedo, Karen and Tim Bakken. 2002. Visiting Women in Prison: Who Visits and
Who Cares? Journal of Offender Rehabilitation 34:67-83.
Chamlin, Mitchell B. and John K. Cochran. 1997. Social Altruism and Crime. Criminology
Christian, Johnna. 2005. Riding the Bus: Barriers to Prison Visitation and Family Management
Strategies. Journal of Contemporary Criminal Justice 21:31-48.
Christian, Johnna, Jeff Mellow, and Shenique Thomas. 2006. Social and Economic Implications
of Family Connections to Prisoners. Journal of Criminal Justice 34:443-452.
Clark, Theresa A. 2001. The Relationship Between Inmate Visitation and Behavior:
Implications for African American Families. Journal of African American Men 6:43-58.
Cobbina, Jennifer E., Beth M. Huebner, and Mark T. Berg. 2012. Men, Women, and
Postrelease Offending: An Examination of the Nature of the Link Between Relational Ties
and Recidivism. Crime and Delinquency 58:331-361.
Cochran, Joshua C. 2014. Breaches in the Wall: Imprisonment, Social Support, and
Recidivism. Journal of Research in Crime and Delinquency 51:200-229.
Cochran, Joshua C. 2012. The Ties that Bind or the Ties that Break: Examining the
Relationships between Visitation and Prisoner Misconduct. Journal of Criminal Justice
Cochran, Joshua C. and Daniel P. Mears. 2013. Social Isolation and Inmate Behavior: A
Conceptual Framework for Theorizing Prison Visitation and Guiding and Assessing
Research. Journal of Criminal Justice 41:252-261.
Cochran, Joshua C., Daniel P. Mears, William D. Bales, and Eric A. Stewart. 2013. Does
Inmate Behavior Affect Post-Release Offending? Investigating the Misconduct-Recidivism
Relationship among Youth and Adults. Justice Quarterly. (Online).
Coleman, James S. 1990. Foundations of Social Theory. Cambridge, MA: Harvard University
Comfort, Megan L. 2003. In the Tube at San Quentin: The “Secondary Prisonization” of
Women Visiting Inmates. Journal of Contemporary Ethnography 32:77-107.
Cullen, Francis T., Cheryl Lero Jonson, and Daniel S. Nagin. 2011. Prisons Do Not Reduce
Recidivism: The High Cost of Ignoring Science. The Prison Journal 91:48S-65S.
Datesman, Susan K. and Gloria L. Cales. 1983. “I’m Still the Same Mommy”: Maintaining the
Mother/Child Relationship in Prison. The Prison Journal 63:142-154.
Duwe, Grant and Valerie Clark. 2013. Blessed Be the Social Tie That Binds: The Effects of
Prison Visitation on Offender Recidivism. Criminal Justice Policy Review. (Online).
Ekland-Olson, Sheldon, Michael Supancic, James Campbell, and Kenneth J. Lenihan. 1983.
Postrelease Depression and the Importance of Familial Support. Criminology 21:253-275.
Ellis, Desmond, Harold G. Grasmick, and Bernard Gilman. 1974. Violence in Prisons: A
Sociological Analysis. The American Journal of Sociology 80:16-43.
Enders, Craig K. and Davood Tofighi. 2007. Centering Predictor Variables in Cross-Sectional
Multilevel Models: A New Look at an Old Issue. Psychological Methods 12:121-138.
Fishman, Laura T. 1990. Women at the Wall: A Study of Prisoners’ Wives Doing Time on the
Outside. Albany: State University of New York Press.
Gaes, Gerald G., Scott D. Camp, Julianne B. Nelson, and William G. Saylor. 2004. Measuring
Prison Performance: Government Privatization and Accountability. New York: AtlaMira.
Garland, David. 1990. Punishment and Modern Society. Chicago, IL: Chicago University
Gendreau, Paul and David Keyes. 2001. Making Prisons Safer and More Humane
Environments. Canadian Journal of Criminology 43:123-130.
Gibson, Chris L. and Marvin D. Krohn. 2013. Handbook of Life-Course Criminology:
Emerging Trends and Directions for Future Research. New York: Springer.
Giordano, Peggy C., Stephen A. Cernkovich, and Meredith D. Pugh. 1986. American Journal of
Glaser, Daniel. 1954. A Reformulation and Testing of Parole Prediction Factors. Unpublished
doctoral dissertation, University of Chicago.
Goetting, Ann and Roy M. Howsen. 1986. Correlates of Prisoner Misconduct. Journal of
Quantitative Criminology 2:49-67.
Gordon, Jill and Elizabeth H. McConnell. 1999. Are Conjugal and Familial Visitations
Effective Rehabilitative Concepts?: Yes. The Prison Journal 79:119-135.
Hagan, John and Ronit Dinovitzer. 1999. Collateral Consequences of Imprisonment for
Children, Communities, and Prisoners. Crime and Justice 26:121-162.
Hairston, Creasie F. 1988. Family Ties During Imprisonment: Do They Influence Future
Criminal Activity? Federal Probation 52:48-52.
Hairston, Creasie F. 1991. Family Ties During Imprisonment: Important to Whom and For
What? Journal of Sociology and Social Welfare 18:87-104.
Hardwick, Virginia L. 1985. Punishing the Innocent: Unconstitutional Restrictions on Prison
Marriage and Visitation. New York University Law Review 60:275-303.
Hensley, Christopher, Mary Koscheski, and Richard Tewksbury. 2002. Does Participation in
Conjugal Visitations Reduce Violence in Mississippi? An Exploratory Study. Criminal
Justice Review 27:52-65.
Hipp, John R., Joan Petersilia, and Susan Turner. 2010. Parolee Recidivism in California: The
Effect of Neighborhood Context and Social Service Agency Characteristics. Criminology
Hirschi, Travis. 1969. Causes of Delinquency. Berkeley: University of California Press.
Hoffman, Heath C., George E. Dickinson, and Chelsea L. Dunn. Communication Policy
Changes in State Adult Correctional Facilities from 1971 to 2005. 2005. Criminal Justice
Holt, Norman and Donald Miller. 1972. Explorations in Inmate-Family Relationships.
California: California Department of Corrections.
Holtfreter, Kristy, Michael D. Reisig, and Merry Morash. 2004. Poverty, State Capital, and
Recidivism among Women Offenders. Criminology and Public Policy 3:185-208.
Jackson, Penny, Donald I. Templer, Wilbert Reimer, and David LeBaron. 1997. Correlates of
Visitation in a Men’s Prison. International Journal of Offender Therapy and Comparative
Jiang, Shanhe and Thomas Winfree, Jr. 2006. Social Support, Gender, and Inmate Adjustment
to Prison Life. The Prison Journal 86:32-55.
Jonson, Cheryl L. 2011. The Impact of Imprisonment on Reoffending: A Meta-Analysis.
Unpublished doctoral dissertation, University of Cincinnati, OH.
Kent, Norman E. 1975. The Legal and Sociological Dimensions of Conjugal Visitation in
Prisons. New England Journal on Prison Law 2:47-65.
La Vigne, Nancy G., Christy Visher, and Jennifer Castro. 2004. Chicago Prisoners’
Experiences Returning Home. Washington, DC: The Urban Institute.
Lahm, Karen F. 2008. Inmate-On-Inmate Assault: A Multilevel Examination of Prison
Violence. Criminal Justice and Behavior 35:120-137.
Land, Kenneth C., Patricia L. McCall, and Lawrence E. Cohen. 1990. Structural Covariates of
Homicide Rates: Are There Invariances Across Time and Social Space? American Journal
of Sociology 95:922-963.
Lembo, James J. 1969. Research Notes: The Relationship of Institutional Disciplinary
Infractions and the Inmate’s Personal Contact with the Outside Community. Criminologica
Liebling, Alison. 1999. Prison Suicide and Prisoner Coping. Crime and Justice 26:283-359.
Listwan, Shelley Johnson, Christopher J. Sullivan, Robert Agnew, Francis T. Cullen, and Mark
Colvin. 2013. The Pains of Imprisonment Revisited: The Impact of Strain on Inmate
Recidivism. Justice Quarterly 30:144-168.
Logan, Charles. 1993. Criminal Justice Performance Measures for Prisons. Pp. 15-59 in
Performance Measures for the Criminal Justice System. Washington D.C.: Bureau of
MacDonald, John M., and Pamela K. Lattimore. 2010. Count Models in Criminology. In
Handbook of Quantitative Criminology, edited by Alex R. Piquero and David Weisburd, pp.
683-698. Springer: New York.
Makarios, Matthew, Benjamin Steiner, and Lawrence F. Travis. 2010. Examining the Predictors
of Recidivism Among Men and Women Released from Prison in Ohio. Criminal Justice and
Maruna, Shadd and Ross Immarigeon. 2004. After Crime and Punishment: Pathways to
Offender Reintegration. Devon, UK: William Publishing.
Mauer, Marc and Meda Chesney-Lind. 2002. Invisible Punishment: The Collateral
Consequences of Mass Imprisonment. New York: New Press.
Mears, Daniel P. 2012. The Prison Experience: Introduction to the Special Issue. Journal of
Criminal Justice 40:345-347.
Mears, Daniel P., Xia Wang, Carter Hay, and William D. Bales. 2008. Social Ecology and
Recidivism: Implications for Prisoner Reentry. Criminology 46:301-340.
Mears, Daniel P., Joshua C. Cochran, Sonja E. Siennick, and William D. Bales. 2012. Prison
Visitation and Recidivism. Justice Quarterly 29:888-918.
Monahan, Kathryn C., Asha Goldweber, and Elizabeth Cauffman. 2011. The Effects of
Visitation on Incarcerated Juvenile Offenders: How Contact with the Outside Impacts
Adjustment on the Inside. Law and Human Behavior 35:143-151.
Moore, Gwen. 1990. Structural Determinants of Men’s and Women’s Personal Networks.
American Sociological Review 55:726-735.
Morris, Robert G., Michael L. Carriaga, Brie Diamond, Nicole L. Piquero, Alex R. Piquero.
2012. Does Prison Strain Lead to Prison Misbehavior? An Application of General Strain
Theory to Inmate Misconduct. Journal of Criminal Justice 40:194-201.
Mumola, Christopher J. 2000. Incarcerated Parents and Their Children. Washington, DC:
U.S. Department of Justice, Bureau of Justice Statistics.
Nagin, Daniel S., Francis T. Cullen, and Cheryl L. Jonson. 2009. Imprisonment and
Reoffending. Crime and Justice 38:115-200.
Ohlin, Lloyd E. 1951. Selection for Parole. New York: Russell Sage.
Orrick, Erin A., John L. Worrall, Robert G. Morris, Alex R. Piquero, William D. Bales, and Xia
Wang. 2011. Testing Social Support Theory: A Multilevel Analysis of Recidivism.
Journal of Criminal Justice 39:499-508.
Osgood, D. Wayne. 2000. Poisson-Based Regression Analysis of Aggregate Crime Rates.
Journal of Quantitative Criminology 16:21-43.
Overton v. Bazzetta, 2162 (S. Ct 2003).Pettit, Becky. 2012. Invisible Men: Mass Incarceration
and the Myth of Black Progress. New York: Russell Sage Foundation.
Parker, Karen F. 2004. Industrial Shift, Polarized Labor Markets and Urban Violence.
Petersilia, Joan. 2003. When Prisoners Come Home: Parole and Prisoner Reentry. New York:
Oxford University Press.
Putnam, Robert D. 2000. Bowling Alone: The Collapse and Revival of American Community.
New York: Simon and Schuster.
Rabe-Hesketh, Sophia and Anders Skondral. 2008. Multilevel and Longitudinal Modeling
Using Stata. College Station, TX: Stata Press.
Reisig, Michael D. and Gorazd Mesko. 2009. Procedural Justice, Legitimacy, and Prisoner
Misconduct. Psychology, Crime, and Law 15:41-59.
Roberts, Dorothy E. 2004. The Social and Moral Costs of Mass Incarceration in African
American Communities. Stanford Law Review 56:1271-1305.
Rose, Dina R. and Todd R. Clear. 2003. Incarceration, Reentry, and Social Capital: Social
Networks in the Balance. Pp. 313-341 in Jeremy Travis and Michelle Waul (Eds.),
Prisoners Once Removed: The Impact of Incarceration and Reentry on Children, Families,
and Communities. Washington, DC: The Urban Institute Press.
Rosenfeld, Richard, Steven F. Messner, and Eric P. Baumer. 2001. Social Capital and
Homicide. Social Forces 80:283-310.
Ross, Jeffrey I. and Stephen C. Richards. 2009. Beyond Bars: Rejoining Society After Prison.
New York: Alpha Books.
Sampson, Robert J. 2013. The Place of Context: A Theory and Strategy for Criminology’s
Hard Problems. Criminology 51:1-32.
Sampson, Robert J. and John H. Laub. 1993. Crime in the Making: Pathways and Turning
Points Through Life. Cambridge, MA: Harvard University Press.
Schafer, N. E. 1978. Prison Visiting: A Background for Change. Federal Probation 30:47-50.
Siennick, Sonja E., Daniel P. Mears, and William D. Bales. 2013. Here and Gone: Anticipation
and Separation Effects of Prison Visits on Inmate Infractions. Journal of Research in Crime
and Delinquency. (Online).
Steffensmeier, Darrell and Emilie Allan. 1996. Gender and Crime: Toward a Gendered Theory
of Female Offending. Annual Review of Sociology 22:459-487.
Steiner, Benjamin, Matthew D. Makarios, and Lawrence F. Travis. 2013. Examining the Effects
of Residential Situations and Residential Mobility on Offender Recidivism. Crime and
Stewart, Eric A. and Ronald L. Simons. 2010. Race, Code of the Street, and Violent
Delinquency: A Multilevel Investigation of Neighborhood Street Culture and Individual
Norms of Violence. Criminology 48:569-605.
Stucky, Thomas D., John R. Ottensmann, and Seth B. Payton. 2012. The Effect of Foreclosures
on Crime in Indianapolis, 2003-2008. Social Science Quarterly 93:602-624.
Sykes, Gresham M. 1958. The Society of Captives. Princeton, NJ: Princeton University Press.
Tasca, Melinda, Marie L. Griffin, and Nancy Rodriquez. 2010. The Effect of Importation and
Deprivation Factors on Violent Misconduct: An Examination of Black and Latino Youth in
Prison. Youth Violence and Juvenile Justice 8:234-349.
Tewksbury, Richard and Matthew DeMichele. 2005. Going to Prison: A Prison Visitation
Program. The Prison Journal 85:292-310.
Travis, Jeremy. 2005. But They All Come Back: Facing the Challenges of Prisoner Reentry.
Washington, D.C.: The Urban Institute Press.
Trulson, Chad R., Matt DeLisi, and James W. Marquart. 2011. Institutional Misconduct,
Delinquent Background, and Rearrest Frequency Among Serious and Violent Delinquent
Offenders. Crime and Delinquency 57:709-731.
Tyler, Tom. 1990. Why People Obey the Law. New Haven, CT: Yale University Press.
Uggen, Christopher and Candace Kruttschnitt. 1998. Crime in the Breaking: Gender
Differences in Desistance. Law and Society Review 32:339-366.
Uggen, Christopher and Sara Wakefield. 2005. Young Adults Reentering the Community from
the Criminal Justice System: The Challenge. Pp. 114-144 in Wayne D. Osgood, Michael E.
Foster, Constance Flanagan, and Gretchen P. Ruth (Eds.), On Your Own without a Net.
Chicago, IL: University of Chicago Press.
Visher, Christy A. 2013. Incarcerated Fathers: Pathways From Prison to Home. Criminal
Justice Policy Review 24:9-26.
Visher, Christy A. and Shannon M. E. Courtney. 2006. Cleveland Prisoners’ Experiences
Returning Home. Washington, DC: Urban Institute.
Visher, Christy A., and Daniel J. O’Connell. 2012. Incarceration and Inmates’ Self Perceptions
About Returning Home. Journal of Criminal Justice 40:386-393.
Wacquant, Loic. 2001. Deadly Symbiosis: When Ghetto and Prison Meet and Mesh.
Punishment and Society 3:95-134.
Wakefield, Sara and Christopher Uggen. 2010. Incarceration and Stratification. Annual Review
of Sociology 36:387-406.
Wang, Xia, Daniel P. Mears, William D. Bales. 2010. Race-Specific Employment Contexts and
Recidivism. Criminology 48:1171-1211.
Weitzer, Ronald and Steven Tuch. 2006. Race and Policing in America: Conflict and Reform.
New York: Cambridge University Press.
Western, Bruce. 2006. Punishment and Inequality in America. New York: Russell Sage
Western, Bruce and Becky Petit. 2002. Beyond Crime and Punishment: Prisons and Inequality.
Wolff, Nancy and Jeffrey Draine. 2004. Dynamics of Social Capital of Prisoners and
Community Reentry: Ties that Bind?. Journal of Correctional Health Care 10:457-490.
Table 1. Descriptive statistics
Variable Mean S.D. Min Max
Sentence length and prior record
Sentence length (months)
Prior prison commitments (count)
Prior convictions (count)
Offense information and time served
Primary offense - drug (1/0)
Primary offense - violent (1/0)
Primary offense - sex (1/0)
Primary offense - property (1/0)
Primary offense - other (1/0)
Time served (months)
Economic disadvantage (z)
Prison admissions (per 1,000)
Charitable revenue ($10k per household)
0.50 0.36 0.01 2.70
Table 2. Multilevel negative binomial regression of prison visitation count on individual- and
county-level characteristics (n = 17,921, 56 counties)
Model 1 Model 2
Independent variables Coef. S.E. Coef. S.E.
Prior prison commitments (count)
Prior convictions (count)
Offense, sentence length, and time served
Primary offense - violent (1/0)
Primary offense - sex (1/0)
Primary offense - property (1/0)
Primary offense - other (1/0)
Sentence length (months)
Time served (months)
Economic disadvantage (z)
Prison admissions (per 1,000)
Charitable revenue ($10k per household)
Note: “White” and “primary offense - drug” are reference variables.
*p < 0.05, **p < 0.01, ***p < 0.001
Figure 1. Predicted counts of visitation by individual- and county-level factors