Abstract
Poor urban communities experience high rates of incarceration and prisoner reentry. This paper examines the residences where former prisoners live after prison, focusing on returns to pre-prison social environments, residential mobility, and the role of intermediate sanctions. Drawing on a unique dataset that follows a cohort of Michigan parolees released in 2003 over time using administrative records, we examine returns to pre-prison environments, both immediately after prison and in the months and years after release. We then investigate the role of intermediate sanctions – punishments for parole violations that are less severe than returning to prison – in residential mobility among parolees. Our results show low rates of return to former neighborhoods and high rates of residential mobility after prison, a significant portion of which is driven by intermediate sanctions resulting from criminal justice system supervision. These results suggest that, through parole supervision, the criminal justice system generates significant residential mobility.
Keywords: incarceration, neighborhood, residential mobility, parole
Introduction
In recent decades the community corrections system has become a key institution in the social and economic life of poor urban neighborhoods across the United States.i The number of Americans under community supervision has increased dramatically, growing from 1.3 million in 1982 to 5.7 million in 2007 (one out of every 45 Americans), before receding slightly to 4.8 million in 2010 (Glaze and Bonczar 2011; Pew Center on the States 2009).ii Despite increasing research in recent years on the connection between skyrocketing rates of incarceration and social inequality (e.g., Alexander 2010; Clear 2007; Pager 2003; Wacquant 2001; Western 2006), there has been relatively little research on how the less-visible but more pervasive system of community corrections affects the well-being of those individuals and communities within its net. Although reliable estimates of the geographic distribution of community supervision are hard to come by, it seems clear that individuals on parole and probation are concentrated in impoverished urban areas (Pew Center on the States 2009; Solomon and Thomson 2004; Cadora; Swartz; and Gordon 2003).
In this paper we explore the neighborhood context, residences, and residential mobility of individuals under the supervision of one part of the community corrections system, former prisoners released on parole. We use unique data on a cohort of parolees released from prison in Michigan in 2003 and followed over time while on parole. Our empirical analysis addresses two critical issues related to the residential outcomes of returning prisoners. The first is whether parolees return to their pre-prison neighborhoods after release. Recent research (Kirk 2009) suggests that parolees who return to the same areas where they lived before prison are at higher risk of recidivating, presumably because they encounter the same criminogenic influences that contributed to their prior offense(s). Some scholars (Cadora, Swartz, and Gordon 2003) have also suggested that a relatively small number of impoverished urban neighborhoods – so-called “million dollar blocks” – send a disproportionately large share of people to prison. Accordingly, we analyze how common it is for parolees to return to the same address and/or neighborhood where they lived before prison, and we also compare the poverty rates of the neighborhoods where parolees lived immediately before and after prison.
In the second part of our analysis, we focus on residential stability among former prisoners, another important predictor of successful reentry and desistance from crime (La Vigne and Parthasarathy 2005). One indicator of residential stability is living in temporary or institutional housing, so we examine the types of housing that parolees obtain, including various forms of private and institutional residences. We pay particular attention to residences that are so-called “intermediate sanctions” imposed by the community corrections system, punishments for parole violations that fall short of returning the parolee to prison, including short-term custody in institutions such as jails, residential treatment centers and programs for technical rule violators. We also explore the extent to which the types of residences where parolees live change as they spend more time in the community, and how much they vary by demographic groups defined by race, gender, and age. Another indicator of residential stability is frequencies of residential moves. We examine the number of residential moves parolees make and the extent to which residential moves are related to moves into and out of intermediate sanctions. We also examine the degree to which moves into and out of intermediate sanctions result in changes in neighborhood context.
Mass Incarceration, Poor Communities, and Residential Mobility
Over the last three decades, the number of individuals incarcerated in prisons and jails in the United States has risen dramatically, from 0.2% of all US residents in 1980 to 0.7% of US residents in 2000 (Western 2006). Whereas in 1975 the population in jails and prisons on any given day was roughly 400,000 people, by 2003 this number had increased more than fivefold to 2.1 million people (Western 2006). As a result, over 600,000 prisoners are released each year (Visher and Travis 2003). Released prisoners are disadvantaged educationally, economically, and socially, and incarceration has been linked to increasing inequality in the US (Pager 2003; Western 2006). Incarceration is disproportionately experienced by young, low-skill, African-American men, and has important consequences for their well-being. For example, declining labor force participation by young black men during the late 1990s, when a strong economy pulled other low-skill workers into the labor market, has been attributed to incarceration and its effects (Holzer, Offner, and Sorensen 2005). Incarceration also increases the likelihood of experiencing severe heath limitations (Schnittker and John 2007), and mortality rates are particularly high in the weeks following release from prison (Binswanger et al. 2007; National Research Council 2007). The steady flow of people into and out of prisons has played a role in increasing inequality in recent decades, primarily by reducing opportunities for employment and lowering wages (Western 2006).
As a consequence of the dramatic rise in incarceration in the United States during the last 30 years, many communities are now grappling with the problem of reintegrating former prisoners. Successful reintegration is challenged by barriers facing former prisoners in housing, employment, and access to services and by former prisoners’ disadvantaged positions with regard to education, work experience, social capital, and mental and physical health (Visher and Travis 2003). The challenges of reintegrating former prisoners do not fall on all communities equally. Poor urban communities bear a disproportionate share of the burden, as incarceration rates are particularly high in such communities (Pew Center on the States 2009; Sampson and Loeffler 2010; Clear 2007), leading to what some analysts have termed “million dollar blocks,” individual city blocks with such high incarceration rates that the government spends over a million dollars a year incarcerating their residents (Columbia Spatial Information Design Lab 2006). Furthermore, some evidence suggests that former prisoners are more likely to return to disadvantaged neighborhoods (Cadora, Swartz, and Gordon 2003; Lynch and Sabol 2004; Solomon and Thomson 2004), where resources and services are stretched thin and law enforcement supervision is high (Fagan, West, and Holland 2003). As a result, the criminal justice system is now as an important an institution for poor communities and their residents as the education system and the labor market. Understanding and meeting the challenges faced by poor communities requires an understanding of the role of the criminal justice system and its effects on individuals and communities.
Although most research on prisoner reentry has focused on the individual-level risk factors for recidivism and unemployment, some scholars have speculated that the neighborhoods where returning prisoners live may play a critical role in successful reintegration (National Research Council 2007). Several studies have now shown that returning prisoners who live in more disadvantaged neighborhoods are more likely to recidivate. Kubrin and Stewart (2006) found that tract-level concentrated disadvantage predicted recidivism in one Oregon county; while Mears and colleagues (2008) analyzed administrative data for the entire state of Florida and found that a county-level measure of resource deprivation was associated with return to prison for a violent or drug-related offense. Hipp, Petersilia, and Turner (2010) found that neighborhood disadvantage, social disorder, and access to social services predicted recidivism among parolees in California.
Another important question is whether moving back to the neighborhood where one lived before prison helps or hinders efforts to desist from crime. One perspective is that returning home is generally a negative influence on parolees, due to the proximity of criminogenic peers and opportunities for returning to crime or substance abuse. Another view is that the social support and social control provided by existing social networks in one’s former neighborhood may be protective. In a study of prisoner reentry in New Orleans after Hurricane Katrina, Kirk (2009) showed that former prisoners who returned to their pre-prison parishes upon their release from prison were more likely to recidivate than those who moved elsewhere.
In addition to the studies of neighborhood effects on criminal trajectories of returning prisoners, there is another stream of research that focuses on the consequences for neighborhoods of losing large numbers of residents to prison and/or absorbing many returning prisoners. Clear (1997) refers to such churning between institutional and community supervision as “coercive mobility” and argues that the residential turnover created by mass incarceration leads to the breakdown of social cohesion in disadvantaged communities. As individuals move into and out of poor neighborhoods, where residential mobility is already high, social networks in the community become sparser, trust in neighbors declines, and collective action becomes less likely. In a study of communities and crime in Tallahassee, Florida, Clear and colleagues (2003) found that neighborhoods receiving returning prisoners at higher rates also had higher crime rates the following year. The relationship between neighborhood population loss due to prison admission and subsequent crime was more complex: moderate rates of population loss reduced crime, but after reaching a critically high level, further increases were associated with higher crime rates. They argued that the cumulative effect of such churning of people back and forth between prison and the community led to a breakdown in community social networks and ultimately eroded the capacity to control crime through informal social control. Relatedly, Hipp and Yates (2009) found that communities with more former prisoners had higher crime rates and that this effect was moderated by neighborhood social capital and voluntary organizations.
Obstacles to Securing Stable Housing among Parolees
The problem of housing insecurity among returning prisoners offers a compelling example of how institutional factors can compound socioeconomic disadvantage in an already marginalized group. In part, the challenge returning prisoners face in finding a place to live is a reflection of their personal economic circumstances, including poor work histories and poor credit histories. Above and beyond these personal circumstances, however, returning prisoners face an additional set of institutional obstacles that make their housing security especially precarious (Geller and Curtis 2011; Metraux, Roman, and Cho 2007; Roman and Travis 2006). First, many private landlords require applicants to disclose their criminal history and are reluctant to accept applications from those with felony convictions (Helfgott 1997; Holzer 1996). Aggravating an already difficult economic situation, many parolees also face mounting fees for supervision, restitution, and child support (Alexander 2010), and their criminal records preclude them from obtaining most types of public assistance, public housing, and housing subsidies (Geller and Curtis 2011; Petersilia 2003). Returning prisoners even face obstacles in seeking temporary shelter with friends or family members who live in public housing. Under the US Department of Housing and Urban Development’s “One Strike and You’re Out” policy (US Department of Housing and Urban Development 1996), public housing tenants can be evicted if any other household members or guests are involved in drugs or other criminal activity on or off the premises, even without the tenant’s knowledge, making them very reluctant to offer assistance to anyone with a criminal record.iii
The conditions of parole also impose restrictions on where returning prisoners can live. For example, sex offenders are usually restricted from moving near schools or daycare centers. Some parolees are also subject to “electronic monitoring,” in which they wear an ankle bracelet, and must live in a house with a working phone that can transmit data (via modem) to the parole officer. In some states (including Michigan) parole agents closely supervise parolee’s living arrangements – often through home visits – and restrict them from living with others who have felony records, as well as any place where there are firearms or drugs on the premises.
Despite the great risks for housing instability among returning prisoners, there has been relatively little research on their living arrangements and residential moves. Some studies have used national surveys of state prisoners to examine the housing status prior to their imprisonment. One such study (Hughes, Wilson, and Beck 2001) found that 12 percent of state prisoners had been homeless at the time of their arrest, while another (Ditton 1999) reported that 9 percent had been living on the street or a shelter at some point during the year prior to their arrest. In one of the few studies to use post-incarceration data on a large sample of returning prisoners, Metraux and Culhane (2004) analyzed longitudinal data on all persons released from New York state prisons and paroled to New York City counties between 1995 and 1998 (n = 48,424) and found that 11.4 percent entered a New York City homeless shelter within two years of release. There have been fewer studies of housing instability and residential mobility among returning prisoners. One study, using survey data collected on 145 Illinois prisoners returning to the City of Chicago (La Vigne and Parthasarathy 2005), found that roughly 72 percent of the sample members stayed in the same residence throughout the observation period of the study (which varied by individual but lasted between one to two years). In a study offering a much less sanguine view of housing security among formerly incarcerated men, Geller and Curtis (2011) analyzed housing instability among fathers from the Fragile Families and Child Wellbeing sample (n = 2,768) and found that men who had been incarcerated faced significantly higher odds of being homeless or experiencing some form of housing insecurity within the last year compared to men with no history of incarceration.
In one of the most comprehensive accounts of parole and prisoner reentry, Petersilia (2003) observed that “we know almost nothing about the exact housing arrangements of former prisoners” (121). Unfortunately, this statement remains an accurate reflection of current research, even nine years later. The current study offers one of the first detailed views of living situations and residential trajectories of a large and representative sample of parolees, followed prospectively over a two-year time period.
Data
Through a collaborative arrangement with the Michigan Department of Corrections (MDOC), we compiled a unique data set based on detailed administrative records on a cohort of 11,064 Michigan prisoners who were placed on parole in Michigan during 2003.iv Over 90 percent of Michigan’s released prisoners are put on parole, one of the higher conditional release rates among American states. Our analyses in this paper are based on a randomly selected sample (n = 3,221) of 29 percent of this population on which we collected more detailed data on post-prison trajectories – including the location of all places of residence – by coding narrative case notes that parole agents update regularly on each parolee.v All of the variables used in our analysis have been extensively cleaned, which involved checking for duplicate records, multiple people with the same ID number, and logical inconsistencies across variables, as well as detailed reading of the case notes where appropriate to resolve discrepancies across sources.
Our analyses in this paper focus on variation by race, sex, age, and neighborhood poverty. Our sample is 8 percent female, 53 percent black, 45 percent white, and 2 percent other (mostly Mexican-American). With regard to age, 18 percent are less than age 25 in 2003, 17 percent are age 26–30, 17 percent are age 31–35, 17 percent are age 36–40, 13 percent are age 41–45, 10 percent are age 46–50, and 7 percent are 51 or older.vi
Address Data
We defined the first post-prison address as the first place where an individual stayed for at least one night and had some “community exposure,” meaning that he or she had unsupervised access to people and places outside of the residence.vii Parolees are required to report all changes of address for the duration of their parole to their parole officers, who in turn are expected to verify this address, assess its appropriateness, and record it in the MDOC database.viii From the case notes we coded dates of all residential moves and periods of unknown residence and absconding, as well as the address of each residence and a description of what type of residence it was.ix We geocoded all of the addresses and linked them to census tracts and their characteristics from the 2000 Census. One-third of our sample had at least one unknown residence, and about nine percent of the average parolee’s time was spent in unknown residences.
The residential histories we analyze in this paper began on the day the parolee was released from prison and ended after a maximum of 24 months or earlier, if one of the following events occurred: (a) the parolee was returned to prison for either a new conviction or parole violation (24 percent of the sample), (b) the parolee was discharged from parole without being returned to prison (38 percent), (c) the parolee died before being discharged or returned to prison (1 percent). None of the above occurred in the first 24 months following release for 37 percent of the sample. These individuals were still on parole in the community 24 months after their release from prison. Although we chose to censor residential histories once the person was returned to prison for the current analysis, we still observe moves to jail, other forms of intermediate sanctions, and periods of absconding that occurred before the residential history was censored for one of the above reasons.
Almost 82 percent of those who eventually discharge are still on parole at 24 months, while about 53 percent of those who eventually return to prison have already done so by 24 months. This means that about 70 percent of those whose residence histories are censored prior to the end of the 24-month study period for this paper are censored because they returned to prison. This is important to keep in mind in interpreting the results presented below. Over time the sample becomes more selective of successful parolees, as those returned to prison are no longer represented in the data.x
No prisoner in Michigan is released without a planned place to live, so living on the streets immediately following release is extremely rare but may be more common later during the parole period. Few parolees have the financial resources to live alone, and few are married (12 percent of those paroled in 2003 in Michigan, according to estimates), so most parolees must either live with parents, other family members, or romantic partners. Parolees are forbidden from moving out of state unless they initiate a lengthy bureaucratic procedure and pay a fee. Moving between counties is allowed but requires prior permission; as such a move would require changing parole offices. In Michigan there is no requirement that the offender must return to the same city or county where she or he was arrested or sentenced.
We collected data on the pre-prison addresses of our sample from hard copies of pre-sentence investigation reports, in which addresses are usually verified by the MDOC agent preparing the report, as well as parole violation reports and parole agent case notes (for those who were on parole prior to their prison term that ended with their parole in 2003). We successfully identified and geocoded pre-prison addresses for all but 1.3 percent of the sample.xi Forty-seven of these addresses, or 1.5 percent, were outside of Michigan. Pre-prison addresses were linked to census tract characteristics for the year in which the individual entered prison.xii
Returning to Pre-Prison Neighborhoods
The first stage of our analysis focuses on the degree to which parolees return to the same neighborhoods where they lived before prison or to neighborhoods similar to their pre-prison neighborhoods in terms of tract poverty rate. In Table 1 we examine this question by looking at the geographic distance between parolees’ pre-prison addresses and the addresses where they resided immediately upon their release from prison and at each six-month interval over the following two years. We classified each post-release residential address based on its geographic distance (in miles) from the pre-prison address.xiii
Table 1.
First Address | 6 Months | 12 Months | 18 Months | 24 Months | Ever in First 24 Months |
|
---|---|---|---|---|---|---|
0–0.5 miles | 31.3% | 30.9% | 27.9% | 27.3% | 24.7% | 40.8% |
0.5–1.0 miles | 3.9% | 3.7% | 4.4% | 4.5% | 4.6% | 9.3% |
1.0–2.0 miles | 8.3% | 9.1% | 9.8% | 10.1% | 10.5% | 19.1% |
2.0–5.0 miles | 16.4% | 18.2% | 19.6% | 18.3% | 20.6% | 33.4% |
> 5 miles | 40.2% | 38.0% | 38.3% | 39.9% | 39.6% | 58.9% |
Number of parolees with defined distances | 3,030 | 2,250 | 1,858 | 1,565 | 1,318 | 3,221 |
Notes: See Appendix Table A3 for residences with undefined distances to pre-prison address
Only 41 percent of parolees ever returned to their pre-prison neighborhood if we define pre-prison neighborhood as within half a mile of their pre-prison address. This is an important corrective to the conventional wisdom that many returning offenders are moving back to the exact same location where they were living before prison. Not only are the majority of former prisoners not returning to their pre-prison neighborhoods, many live quite far from their pre-prison neighborhoods. At any given time point over the two year observation period, over 56 percent of all parolees in the sample lived more than two miles away from their pre-prison home, and over 38 percent lived more than five miles away. Moreover, the percentage of parolees living within half-a-mile of their pre-prison residence declined slightly over time (from 31 percent at the first address to 25 percent at 24 months), while an increasing percentage lived two to files miles from their pre-prison address (16 percent initially compared to 21 percent at 24 months).xiv
Just because relatively few parolees returned to their pre-prison neighborhoods does not mean that they encountered dramatically different neighborhood contexts after prison compared to those where they lived before prison. Thus, we compared the concentration of poverty – classified as low (less than 10 percent), medium (10–20 percent) and high (over 20 percent) in each parolee’s pre-prison neighborhood to that in their first post-prison neighborhood. Table 2 displays these comparisons, separately by the race of the parolee. The majority of parolees returned to neighborhoods classified in the same poverty category as those where they lived before prison. However, there was also considerable variation between pre-prison and post-prison neighborhoods. Over 40 percent of blacks and over 43 percent of whites lived in a different poverty category before prison than after prison.
Table 2.
a. Black Parolees Post-Prison → Pre-Prison ↓ |
Low- poverty (< 10%) |
Medium Poverty (10–20%) |
High- poverty (> 20%) |
Row Total |
Low-poverty (< 10%) | 72 35.5% |
64 31.5% |
67 33.0% |
203 100.0% |
Medium Poverty (10–20%) | 58 14.8% |
213 54.2% |
122 31.0% |
393 100.0% |
High-poverty (> 20%) | 85 8.3% |
262 25.4% |
683 66.3% |
1,030 100.0% |
Column Total | 215 13.2% |
539 33.1% |
872 53.6% |
1,626 100.0% |
b. White Parolees Post-Prison → Pre-Prison ↓ |
Low- poverty (< 10%) |
Medium Poverty (10–20%) |
High- poverty (> 20%) |
Row Total |
Low-poverty (< 10%) | 436 58.2% |
192 25.6% |
121 16.2% |
749 100.0% |
Medium Poverty (10–20%) | 112 25.3% |
249 56.2% |
82 18.5% |
443 100.0% |
High-poverty (> 20%) | 54 20.7% |
68 26.1% |
139 53.3% |
261 100.0% |
Column Total | 602 41.4% |
509 35.0% |
342 23.5% |
1,453 100.0% |
In addition, there were striking racial differences in the degree to which parolees experienced continuity in exposure to concentrated poverty before and after prison. Among black parolees, the correspondence between pre- and post-prison neighborhood poverty rates was highest among those who lived in high-poverty neighborhoods before prison (66 percent of blacks in high-poverty neighborhoods before prison moved back to high-poverty neighborhoods after prison, whereas only 36 percent of blacks who lived in low-poverty neighborhoods before prison moved back to low-poverty neighborhoods). We found the opposite pattern among white parolees, where the probability of living in a post-prison neighborhood with the same poverty rate as the pre-prison neighborhood was highest for those who lived in low-poverty neighborhoods before prison (58 percent of whites who lived in low-poverty neighborhoods before prison moved back to a low-poverty neighborhood, whereas 53 percent of whites who lived in high-poverty neighborhoods before prison moved back to high-poverty neighborhoods). The racial disparities are even more striking when we compare the distribution of neighborhood poverty of blacks to whites either before or after prison, which shows that 63 percent of blacks lived in high-poverty neighborhoods before prison compared to only 19 percent of whites, while 54 percent of blacks moved to high-poverty neighborhoods immediately after their release from prison, compared to only 24 percent of whites.
Post-Prison Residential Mobility and Intermediate Sanctions
Above we examined residential mobility between pre and post-prison residences and neighborhoods. The next part of our analysis focuses on residential instability among parolees after prison. We begin by examining the types of residences where parolees live, since temporary or institutional housing is an indicator of residential instability. We are also interested in the degree to which parolees reside in “intermediate sanction” residences mandated by community supervision, as these are another potential source of residential instability.
Table 3 presents categories of institutional and non-institutional residences where parolees live and shows how the distribution of residence types changes with time (the cells show how many subjects lived in each type of residential setting at a specific number of months after their release from prison). Over 70 percent of subjects moved into a private residence at release, but the proportion living in private residences increased only slightly thereafter. A smaller but still substantial number (12 percent) of subjects were released to correctional centers operated by MDOC, where they have the ability to leave the facility to work, look for a job, or to visit family, but they also have a nightly curfew and are sometimes kept on electronic monitoring. Our residence typology distinguishes between these correctional centers, which are typically but not exclusively used as an intermediate step between prison and living in the community on parole, and other custodial centers that are commonly used as intermediate sanctions for probation detention, technical rule violation, and/or reentry programming.xv Intermediate sanctions are responses by the criminal justice system to proscribed behavior by the parolee that falls short of re-incarceration in prison. Sometimes these behaviors are illegal, such as drug use or petty theft, and sometimes they are violations of the rules of parole, such as alcohol consumption, curfew violations, failure to report to one’s parole officer, association with other parolees, or contact with crime victims. Intermediate sanctions are used to punish parolees for minor crimes or rule violations without returning them to prison, and they are often intended to stop such behavior from escalating to more serious offenses. For example, a parolee who fails to report to his parole officer and is suspected of using drugs may be sent to a residential drug treatment program or a technical rule violation center for a week or two in order to “detox.” Typically, a parolee will not receive such a sanction for a rule violation until he/she has accumulated a number of infractions or displays behaviors consistent with prior crimes. Only a small fraction (1 percent) of sample members were released to probation detention, TRV, or reentry programming centers, but by a year after release 2.4% were living in such a center. Another common intermediate sanction is spending time in jail. This occurs when a parolee is arrested by the police for a minor crime and either serves a short jail sentence (e.g., 90 days) or has the charges dropped before prosecution. Parolees may also spend a few days in jail as an intermediate sanction at the behest of parole agents. The proportion living in jail peaks at almost six percent at one-year after release.
Table 3.
Residence Type (Percent of Non- censored) |
First Address | 6 Months | 12 Months | 18 Months | 24 Months |
---|---|---|---|---|---|
Private Residence | 72.0% (2,335) |
75.5% (2,097) |
74.3% (1,771) |
75.0% (1,498) |
75.8% (1,261) |
State/Local Institution | |||||
Correctional Center | 11.8% (383) |
2.5% (70) |
1.3% (32) |
0.6% (12) |
0.5% (8) |
Probation Detention, TRV, or Reentry Programming | 1.8% (37) |
2.7% (98) |
2.4% (80) |
3.0% (47) |
2.7% (46) |
Jail | 4.4% (121) |
5.9% (141) |
5.6% (112) |
4.1% (69) |
|
Commercial Placement | |||||
Transitional Housing | 1.9% (61) |
1.0% (29) |
1.0% (24) |
1.0% (20) |
1.2% (20) |
Treatment Program | 1.8% (58) |
2.7% (75) |
2.4% (57) |
3.0% (60) |
2.7% (45) |
Hotel | 5.2% (170) |
0.5% (14) |
0.5% 12) |
0.6% 12) |
0.5% (8) |
Other | |||||
Hospital | 0.2% (5) |
0.3% (9) |
0.3% (6) |
0.5% (9) |
0.5% (8) |
Shelter | 3.2% (103) |
0.8% (21) |
0.5% (13) |
0.7% (13) |
0.8% (14) |
Homeless | 0.1% (2) |
0.2% (5) |
0.1% (1) |
0.1% (2) |
|
Unknown Residence | 2.1% (69) |
8.6% (240) |
10.2% (243) |
10.7% (214) |
11.0% (183) |
Censored (% of Total) | 13.8% (445) |
26.0% (837) |
38.0% (1,223) |
48.3% (1,557) |
|
Total | 100% (3,221) |
100% (3,221) |
100% (3,221) |
100% (3,221) |
100% (3,221) |
n = 3,221 individuals; Note: TRV = Technical Rule Violation Center
Other common places for former prisoners to live immediately after prison were hotels (5 percent) and homeless shelters (3 percent) – both are typical destinations for parolees who have no private residence where they can return – but the proportion of parolees in these places declined over time. The “homeless” category captures people living on the street and is extremely uncommon in our data, although it is possible that some of the subjects with unknown residences were homeless, unknown to their parole agents. Transitional Housing and Treatment Programs house parolees under programs operated by private entities, typically non-profits under contract with MDOC. Treatment programs can also be used as an intermediate sanction by parole officers. The category of unknown residence captures instances when the parole agent either does not know where the individual is living (e.g., because the parolee has absconded) or does not record the type of residence associated with the address. The frequency of unknown residences increases considerably over time but never exceeds 11 percent of residences. We categorize subjects as “censored” in this table if they had been discharged from parole or returned to prison. Overall, this table documents a relatively high degree of use of institutional housing among former prisoners. Because such housing is intended to be temporary, its frequency is one piece of evidence of a high degree of residential instability in this population.
Table 4 shows how exposure to each of these residential settings varies across demographic subgroups, displaying both the percentage of sample members who ever resided in each type of residence and the percentage of time they spent in each type during the observation period. Our focus here is on the prevalence of so-called intermediate sanctions. Table 4 shows that most parolees experience some type of intermediate sanction while on parole. For example, almost half of parolees in the sample spent some time in jail while on parole, 29 percent spent some time in a treatment program, 26 percent in a correctional center, and 25 percent in a center for probation detention, technical rule violation (TRV), or reentry programming. Overall, 65 percent of parolees experience at least one of these intermediate sanctions, and 53 percent experienced at least one intermediate sanction other than jail. Moreover, intermediate sanctions are common among all subgroups of parolees. Women are somewhat more likely than men to be sent to treatment and less likely to be sent to detention, TRV, or reentry programming centers. Because such facilities are gender segregated, this difference may simply reflect the availability of sanction options for women in certain geographic areas of the state. Jail and probation detention, TRV, or reentry programming centers are slightly more common among younger parolees.
Table 4.
Ever Resided in Residence Type | ||||||||||
Residence Type | All Parolees |
Whites | Blacks | Men | Women | Age 18– 25 |
Age 26– 35 |
Age 36– 45 |
Over 45 |
|
Intermediate Sanctions | ||||||||||
Jail | 49.1% | 47.7% | 50.5% | 49.2% | 48.2% | 56.0% | 50.2% | 46.1% | 44.8% | |
Treatment Program | 28.3% | 28.7% | 27.8% | 27.3% | 39.4% | 24.7% | 24.8% | 32.5% | 31.4% | |
Correctional Center | 25.2% | 23.3% | 27.0% | 25.2% | 25.9% | 25.0% | 25.3% | 24.8% | 26.1% | |
Probation Detention, TRV, or Reentry Programming | 23.4% | 20.2% | 26.5% | 23.9% | 17.9% | 28.3% | 23.2% | 22.9% | 19.6% | |
Any Intermediate Sanction | 64.9% | 63.1% | 66.5% | 64.9% | 64.9% | 69.7% | 65.0% | 62.6% | 63.5% | |
Any Sanction Other than Jail | 52.5% | 49.7% | 55.0% | 52.2% | 56.2% | 54.7% | 50.9% | 52.9% | 52.8% | |
Other Residence Types | ||||||||||
Private Residence | 96.2% | 96.0% | 96.3% | 96.1% | 97.2% | 97.8% | 97.5% | 95.8% | 92.6% | |
Transitional Housing | 6.2% | 7.5% | 5.2% | 5.8% | 11.2% | 3.4% | 4.7% | 7.7% | 9.8% | |
Hospital | 9.0% | 8.7% | 9.3% | 8.5% | 15.9% | 3.9% | 7.0% | 10.8% | 15.4% | |
Hotel | 8.5% | 10.4% | 7.0% | 8.4% | 9.6% | 4.4% | 6.7% | 11.1% | 11.6% | |
Shelter | 8.9% | 9.5% | 8.4% | 8.7% | 10.4% | 4.6% | 5.7% | 11.4% | 15.1% | |
Homeless | 1.2% | 1.0% | 1.5% | 1.2% | 2.0% | 0.3% | 1.0% | 1.7% | 1.8% | |
Unknown Residence | 32.9% | 27.0% | 37.8% | 32.4% | 38.7% | 31.1% | 32.1% | 33.4% | 35.4% | |
Percent of Time in Residence Type for Average Parolee | ||||||||||
All Parolees |
Whites | Blacks | Men | Women | Age 18– 25 |
Age 26– 35 |
Age 36– 45 |
Over 45 |
||
Intermediate Sanctions | ||||||||||
Jail | 4.6% | 4.6% | 4.5% | 4.7% | 3.7% | 5.8% | 4.4% | 4.3% | 4.0% | |
Treatment Program | 3.0% | 3.4% | 2.7% | 2.9% | 4.2% | 2.1% | 2.5% | 3.6% | 3.8% | |
Correctional Center | 1.9% | 1.8% | 1.9% | 1.9% | 1.9% | 1.8% | 1.7% | 2.2% | 1.7% | |
Probation Detention, TRV, or Reentry Programming | 2.8% | 2.7% | 2.9% | 2.9% | 1.9% | 4.2% | 2.8% | 2.6% | 1.9% | |
Any Intermediate Sanction | 12.3% | 12.5% | 12.1% | 12.3% | 11.7% | 13.9% | 11.4% | 12.7% | 11.4% | |
Any Sanction Other than Jail | 7.7% | 7.9% | 7.5% | 7.7% | 8.0% | 8.1% | 7.0% | 8.4% | 7.4% | |
Other Residence Types | ||||||||||
Private Residence | 74.4% | 76.7% | 72.4% | 74.5% | 73.2% | 77.4% | 77.8% | 71.9% | 68.7% | |
Transitional Housing | 1.3% | 1.4% | 1.2% | 1.2% | 2.4% | 0.3% | 0.9% | 1.5% | 2.9% | |
Hospital | 0.4% | 0.3% | 0.5% | 0.4% | 0.5% | 0.1% | 0.2% | 0.4% | 1.2% | |
Hotel | 1.6% | 1.9% | 1.3% | 1.6% | 1.0% | 0.9% | 1.0% | 2.2% | 2.5% | |
Shelter | 1.3% | 1.5% | 1.2% | 1.3% | 1.3% | 0.6% | 0.6% | 2.1% | 2.2% | |
Homeless | 0.1% | 0.1% | 0.1% | 0.1% | 0.1% | 0.0% | 0.1% | 0.2% | 0.2% | |
Unknown Residence | 8.6% | 5.6% | 11.2% | 8.5% | 10.0% | 6.8% | 8.2% | 8.9% | 10.9% | |
Total | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% |
n = 3,221 individuals; Note: TRV = Technical Rule Violation Center
How much time do parolees spend in intermediate sanctions? The bottom panel of Table 4 shows the percent of time spent in each residence type. Of the intermediate sanctions, the most time is spent in jails. Parolees on average spend about five percent of their nights in jail, or one out of every 20 nights while on parole. Treatment programs are the second most common, followed by detention, TRV and reentry programming, and then by correctional centers. These relative rankings are similar across subgroups. Overall, about 12 percent of nights are spent in a residence for an intermediate sanction, suggesting that although common, stays in sanction residences are relatively short.
We next turn to another measure of residential instability, the number of residential moves per year. We ask how residences in intermediate sanction facilities are related to residential mobility among parolees. Table 5 shows two measures of residential mobility, the typical number of moves per year and the cumulative distance moved during the observation period. This table also shows the degree to which residential moves are associated with moves into and out of intermediate sanctions. The median parolee experiences 2.6 moves per year, or one move every four and a half months. This is a very high level of residential mobility, a level not seen in most other populations. By comparison, the conventional threshold for a high degree of residential instability is more than one move per year (Geller and Curtis 2011).
Table 5.
All Parolees | Whites | Blacks | Men | Women | Age 18–25 | Age 26–35 | Age 36–45 | Over 45 |
|
---|---|---|---|---|---|---|---|---|---|
Moves Per Year (Median Parolee) | 2.59 | 2.62 | 2.58 | 2.54 | 3.00 | 3.00 | 2.50 | 2.65 | 2.44 |
Sanction Moves Per Year | 0.61 | 0.50 | 0.72 | 0.61 | 0.68 | 1.00 | 0.64 | 0.53 | 0.50 |
Proportion Moves due to Sanctions | 0.24 | 0.19 | 0.28 | 0.24 | 0.23 | 0.33 | 0.25 | 0.20 | 0.20 |
Cumulative Miles Moved (Median Parolee) | 25.50 | 36.43 | 19.88 | 24.37 | 38.47 | 33.72 | 23.59 | 23.66 | 24.28 |
Cumulative Miles Moved due to Sanctions | 7.79 | 6.58 | 8.55 | 7.86 | 7.38 | 11.21 | 8.21 | 6.50 | 5.77 |
Proportion Miles Moved Due to Sanctions | 0.31 | 0.18 | 0.43 | 0.32 | 0.19 | 0.33 | 0.35 | 0.27 | 0.24 |
n = 3,221 individuals
Rates of residential mobility are similar for blacks and whites and for men and women, but younger parolees tend to experience more moves than older parolees. About one-quarter of residential moves are associated with moves into and out of intermediate sanction residences. This proportion is slightly higher for blacks (28 percent) and for younger parolees. Indeed, the higher rate of residential moves among parolees age 18 to 25 seems to be almost entirely attributable to intermediate sanction moves. Excluding intermediate sanction moves equalizes the number of moves across age groups at around two moves per year. The cumulative miles measure of residential mobility tells a similar story, although there is greater variability in miles moved. Whites tend to move longer distances than blacks, reflecting their greater concentration in the suburbs and rural areas, so the proportion of the total distance moved due to sanctions is lower among whites. Women move further than men overall, so the proportion of the total distance moved due to sanctions is lower for women. The proportion of distance moved due to intermediate sanctions is also lower for older age groups.
What are the consequences of intermediate sanctions for the stability of a parolee’s residence over time? We answer this question by examining the rate of return to the pre-sanction address following release from an intermediate sanction facility or center.xvi As shown in Table 6, Parolees return to the previous private residence following intermediate sanctions only three-quarters of the time. Returns are slightly more common among blacks than whites and among men compared to women. The rate of return seems to vary somewhat by type of sanction, with correctional center sanctions most often leading to returns to the previous private residence and detention, TRV, and reentry programming least often leading to returns (when an individual experiences multiple sanctions in sequence, we use the last sanction in the sequence to determine type). These return rates correspond to the typical sanction length, with longer sanctions associated with less likelihood of return. Parolees living in high-poverty neighborhoods before a sanction are least likely to return to the same address after the sanction, particularly when those sanctions are treatment programs or jail. Together, the results presented in Tables 4 through 6 indicate a considerable amount of residential mobility is generated by intermediate sanctions.
Table 6.
Type of Sanction | |||||
---|---|---|---|---|---|
Treatment Program |
Jail | Correctional Center |
Probation Detention, TRV, or Reentry Programming |
All Sanctions |
|
Percent of Sanctions | 24.1% | 37.6% | 20.3% | 17.9% | 100.0% |
Median Days in Sanction | 35 | 20 | 5 | 98 | 24 |
Return to Pre-Sanction Neighborhood | |||||
All Parolees | 74.7% | 77.1% | 87.7% | 64.5% | 76.5% |
Whites | 70.6% | 76.7% | 82.5% | 54.7% | 72.6% |
Blacks | 77.8% | 77.2% | 90.7% | 70.1% | 79.2% |
Men | 75.2% | 77.9% | 88.0% | 65.2% | 77.1% |
Women | 70.8% | 65.1% | 82.2% | 50.0% | 68.1% |
Age 18–25 | 76.0% | 80.1% | 86.5% | 66.7% | 77.8% |
Age 26–35 | 75.4% | 76.9% | 89.4% | 58.5% | 76.3% |
Age 36–45 | 75.0% | 75.8% | 86.0% | 70.8% | 76.8% |
Over 45 | 71.9% | 75.2% | 88.4% | 60.1% | 74.8% |
Pre-Sanction Neighborhood: | |||||
Low-poverty (< 10%) | 75.5% | 79.6% | 90.3% | 63.6% | 78.2% |
Medium Poverty (10–20%) | 80.3% | 81.6% | 87.2% | 63.0% | 79.3% |
High-poverty (> 20%) | 71.6% | 72.6% | 86.6% | 65.7% | 74.1% |
n = 4,614 sanctions; Note: TRV = Technical Rule Violation Center
The implications of returning to a pre-sanction address after the sanction likely depend on the neighborhood where the address is located. Higher-poverty neighborhoods are expected to present fewer opportunities for employment and greater risks of involvement in drug abuse or crime. Table 7 examines the pre-sanction and post-sanction neighborhoods among individuals who changed addresses following a sanction. The top panel presents results for blacks and the bottom panel presents results for whites. Among both blacks and whites who moved residences after an intermediate sanction, there is evidence that post-sanction neighborhoods have higher poverty rates than pre-sanction neighborhoods. For instance, among blacks who were living in a low-poverty neighborhood before the sanction, almost 60 percent moved to high-poverty neighborhoods after the sanction, while only 10 percent of blacks originating in high-poverty neighborhoods moved to low-poverty neighborhoods after the sanction. Similar though weaker patterns are evident among whites. Over 30 percent of whites who lived in a low-poverty neighborhood prior to the sanction moved to a high-poverty neighborhood after the sanction. Of those who originated in a high-poverty neighborhood, only 26 percent moved to a low-poverty neighborhood after the sanction.
Table 7.
a. Black Parolees Post-Sanction → Pre-Sanction ↓ |
Low- poverty (< 10%) |
Medium Poverty (10– 20%) |
High- poverty (> 20%) |
Row Total |
Low-poverty (< 10%) | 10 13.9% |
19 26.4% |
43 59.7% |
72 100.0% |
Medium Poverty (10–20%) | 21 18.1% |
28 24.1% |
67 57.8% |
116 100.0% |
High-poverty (> 20%) | 34 9.7% |
54 15.4% |
263 74.9% |
351 100.0% |
Column Total | 65 12.1% |
101 18.7% |
373 69.2% |
539 100.0% |
b. White Parolees Post-Sanction → Pre-Sanction ↓ |
Low- poverty (< 10%) |
Medium Poverty (10– 20%) |
High- poverty (> 20%) |
Row Total |
Low-poverty (< 10%) | 107 46.5% |
53 23.0% |
70 30.4% |
230 100.0% |
Medium Poverty (10–20%) | 43 33.6% |
50 39.1% |
35 27.3% |
128 100.0% |
High-poverty (> 20%) | 41 26.3% |
35 22.4% |
80 51.3% |
156 100.0% |
Column Total | 191 37.2% |
138 26.8% |
185 36.0% |
514 100.0% |
n = 1,053 sanctions in which parolee did not return to pre-sanction address
Conclusion
The United States is now in an era of “mass incarceration” (Mauer 1999, Garland 2001), with incarceration rates that are unprecedented in our own history and compared to other nations. Incarceration is disproportionately experienced by poor urban minority men and its effects extend beyond these individuals to their communities. Rates of incarceration and community supervision are so high in some poor urban neighborhoods that the criminal justice system has become a key institution that structures social and economic life in these communities. In this paper, we draw on unique data on a cohort of parolees in Michigan to offer one of the first detailed portraits of the residential trajectories of returning prisoners. We focus on the extent to which former prisoners return to their pre-prison neighborhoods, on the types of neighborhoods and residences where they live, and on the role that intermediate sanctions play in generating residential mobility. We are aware of no prior study that examines pre-prison residences and neighborhoods, residential histories after prison, the relationship between the two, or the role of intermediate sanctions in residential mobility.
Two main sets of findings emerged from this analysis that challenge, in some ways, conventional wisdom about the living situations and housing instability of returning prisoners and emphasize the ways that both are affected by the institutions of the criminal justice system. First, our results sharply conflict with what we perceive to be the conventional wisdom regarding the likelihood that former prisoners will return to former neighborhoods after prison. In fact, less than one-third of parolees in our sample returned to an address within a half mile of their pre-prison residences after release, and by two years after release, less than one-quarter were living within a half mile of their pre-prison address. The implications of these results for former prisoners are far from clear. On the one hand, new homes and new communities after prison may mean lack of access to social and economic support that is potentially important for reentry and reintegration. On the other hand, returning to “old places and old faces,” environments that were potentially criminogenic in the past, may increase opportunities for and tendencies toward renewed involvement in substance use and crime. The implications of returning “home” after prison likely vary by the characteristics of that environment. Moreover, high rates of residential mobility mean that future studies need to look beyond the first neighborhood after release in assessing the effects of neighborhood context on the outcomes of former prisoners, and further research is required to understand the implications of residential mobility and the predictors of neighborhood and household environments among former prisoners.
Why don’t more former prisoners return to their pre-prison residences or neighborhoods? Although this question lies beyond the scope of the analysis for this paper, we offer some hypotheses based on qualitative interviews we conducted with 24 former prisoners released in Southeast Michigan in late 2007 and early 2008. First, the families and communities from which former prisoners come themselves have higher than average rates of residential mobility. During the time a family member is in prison, the household may move. This is particularly likely when the prisoner provided the main source of household income or owned or rented the family’s dwelling. Second, family members may be unwilling to continue to support a former prisoner, particularly when he or she has been in and out of prison multiple times or brings substance abuse or other criminal behavior into the household. Family relationships may fray with frequent contact with the criminal justice system and frequent and prolonged separation due to incarceration, particularly for extended kin. In such cases, treatment programs, corrections centers, hotels, or homeless shelters may be the only post-release housing options, and they are less likely to be in or near pre-prison neighborhoods. Third, former prisoners preparing for release may not be well-served by returning to pre-prison social environments. Sometimes the former prisoner recognizes this for himself and intentionally stays away from potentially criminogenic environments. In other cases, parole boards or parole agents may make this determination and require or encourage a new start in a new environment.
A second major finding concerns the volume of residential mobility among parolees, and the degree to which this reflects the experience of parole supervision through intermediate sanctions. For example, 65 percent of parolees in our sample were moved away from their residence at least once for an intermediate sanction. Also, former prisoners experienced very high rates of residential mobility on average – higher than any other population of which we are aware – and roughly one-quarter to one-third of this mobility was generated by the criminal justice system through intermediate sanctions such as jail, treatment programs, and residential facilities for parole rule violators. Moreover, a substantial share of parolees who experienced an intermediate sanction (between one-quarter to one-third, depending on the sanction) did not return to their prior residence after the sanction. In short, because parolees experience considerable residential mobility associated with intermediate sanctions, the effects of the criminal justice system on residential turnover are likely more extensive than previously recognized, extending beyond moves to and from prison.
We are agnostic about the implications of this residential mobility for community wellbeing. It could bring further social disorganization to already disadvantaged communities, but Clear’s coercive mobility theory, particularly the argument that extremely high levels of movement to prison actually increase crime, has not been subjected to many empirical tests nor has prior research on coercive mobility considered residential mobility due to intermediate sanctions. Moreover, we note that intermediate sanctions are intended to remove former prisoners temporarily from communities before they progress to more serious crimes. They represent both an alternative to the more consequential sanction of returning a parolee to prison and an attempt by parole agents to prevent crime before it happens or before substance use and more minor crimes progress to more serious crimes. Whether intermediate sanctions benefit or harm either individual or community are open questions. The frequency with which they are experienced, however, suggests that these are potentially important questions for future research.
Moreover, because most prisoners are not returning to their former residences, many of the parolees who enter disadvantaged neighborhoods do so as newcomers and are therefore less likely to have social resources to buffer the detrimental effects of living in disadvantaged neighborhoods. This also means that the coercive mobility that comes from moves to and from prison may be more consequential for social cohesion than previously recognized, since it is not always the same individuals who are leaving and then returning to neighborhoods with high rates of incarceration. Indeed, there is something of a paradox when it comes to residential mobility and the neighborhood environments of former prisoners. Although these individuals experience high rates of residential mobility, a small proportion of neighborhoods house the vast majority of former prisoners. This is only possible if former prisoners are moving frequently from one disadvantaged neighborhood to another. Which former prisoners are able to escape high-poverty neighborhoods is an important question for future research.
One strength of our study is its ability to draw data from multiple cities, metro areas, and rural areas for an entire state, but our analysis is limited to a single state, and social and economic conditions as well as criminal justice policies vary considerably from state to state. Michigan is characterized by high unemployment, by declining opportunities for employment in low skill positions, and by high rates of racial and economic residential segregation. Michigan also has few Latino or Asian residents, so we can only analyze racial differences between blacks and whites. In terms of criminal justice policies and practices, we note that Michigan’s rates of incarceration and parole are close to the national averages. Michigan also accounts for a nontrivial share (4–5 percent) of the nation’s parole population. Our findings regarding the importance of intermediate sanctions may be particularly sensitive to state-specific resources and policies related to parole supervision, particularly parole revocation. The rate of return to prison among Michigan parolees was 17 percent in 2006, the same as the national average for state parolees (Sourcebook of Criminal Justice Statistics Online 2011). Yet parole revocation rates are likely subject to countervailing forces. For example, more stringent supervision may result in higher revocation rates, but more stringent supervision coupled with greater use of intermediate sanctions may result in lower parole revocation rates.
Supplementary Material
Acknowledgments
This research was funded by the University of Michigan Center for Local, State, and Urban Policy, the National Poverty Center at the University of Michigan, the Russell Sage Foundation, the National Institute of Justice, and the Eunice Kennedy Shriver National Institute of Child Health and Human Development. We thank Paulette Hatchett, our collaborator at the Michigan Department of Corrections, for facilitating access to the data and for advice on the research design, and we thank Steve Heeringa and Zeina Mneimneh for advice on the sample design. Charley Chilcote, Brenda Hurless, Bianca Espinoza, Andrea Garber, Jessica Wyse, Jonah Siegal, Jay Borchert, Amy Cooter, Jane Rochmes, Jon Tshiamala, Katie Harwood, Elizabeth Sinclair, Carmen Gutierrez Joanna Wu, Clara Rucker, Michelle Hartzog, Tyrell Connor, Madie Lupei, Elena Kaltsas, Brandon Cory, and Elizabeth Johnston provided excellent research assistance.
Biographies
David J. Harding is Associate Professor of Sociology and Public Policy and Research Associate Professor at the Institute for Social Research at the University of Michigan.
Jeffrey D. Morenoff is Professor of Sociology and Research Professor at the Institute for Social Research at the University of Michigan.
Claire W. Herbert is a PhD Candidate in the Department of Sociology at the University of Michigan.
Footnotes
A prior version of this paper was presented at the conference on Rethinking Urban Poverty for the 21st Century City: Institutional and Organizational Perspectives, March 10–11, 2011 at the University of Chicago.
“Community corrections” is an umbrella term that refers to the network of state, federal, and private agencies involved in supervising offenders who have either been sentenced to some form of community supervision (usually known as probation) as an alternative to incarceration or released to the community after serving time in prison (usually known as parole).
These numbers only count offenders on probation or parole, but a recent study (Taxman et al. 2007) estimated that up to one million additional offenders are under community supervision in more specialized programs, such as alternative sentencing units or mandatory drug treatment programs.
In 2002 the U.S. Supreme Court upheld the constitutionality of such evictions in Department of Housing and Urban Development v. Rucker, 535 U.S. 125.
Whereas jails are run by local cities and counties and hold individuals with sentences less than one or two years or awaiting trial, prisons are run by the states or the federal government and hold individuals who have longer sentences.
To ensure adequate variation in the geographic locations and characteristics of the first neighborhoods to which our sampled cases returned, we employed a two-stage cluster sampling design (in which parolees are clustered within the census tracts containing their first address) with probabilities proportionate to size. We successfully identified and geocoded the first residential addresses of all but 25 parolees (0.2 percent) in the cohort. In the first stage, we systematically sampled census tracts with probability proportionate to their size (i.e., the number of parolees who returned to each tract). In the second stage we sampled individuals within each selected tract with probability inversely proportionate to the tract selection rate. When the first- and second-stage selection rates are multiplied together, the sampling probability is equal for every individual (Groves et al. 2004). This approach also ensures that the final sample size of parolees remains the same no matter which tracts were sampled in the first stage. Some tracts had fewer than the desired within-tract sample size of returning parolees. In such cases, we combined geographically proximate tracts that were in the same county and had similar socioeconomic characteristics until the number of parolees in the combined units equaled or exceeded the expected within-tract sample size (eight). Another issue is that some tracts had a large number of parolees, which meant that their first stage probability of being selected exceeded 1.0. Following the method suggested by Groves et al. (2004, 124), we included all such tracts in our sample (but removed them from the list from which the stage one sample is drawn), and directly selected parolees from them at random at the overall sample rate (1/3). Parolees whose addresses were missing or could not be geocoded (n = 25) were sampled separately, at the same overall rate (1/3). We excluded from this analysis eight sampled individuals who absconded from parole immediately after release and were quickly re-incarcerated and therefore have no post-prison residential information.
Sample descriptive statistics are provided in Appendix Table A1.
Those who were paroled to institutions offering no exposure to the community, such as hospitals, in-patient treatment centers, or county jails, were assigned the first subsequent non-institutional address. Homeless individuals were assigned the census tract of the shelter or mission where they were staying (no parolees were living on the streets immediately after their release, as a prisoner must have a place to live before being paroled). Also, about 15 percent of the parolees in our sample were released from prison before their parole date because they were moved to a correctional center where they had community exposure or were placed on electronic monitoring (and technically not yet considered to be on parole).
Failure to keep one’s parole agent informed of one’s address is a parole violation, and parole agents are required to verify residence information provided by parolees, so parolees have a strong incentive to provide address information. No doubt there are some parolees who do not report their true place of residence, and there are some parole agents who are less careful than others in recording this information. Nonetheless, our preliminary research suggests that the addresses in the case notes are surprisingly accurate. We are conducting a longitudinal qualitative study of 24 former prisoners who were interviewed once in prison prior to release and at regular interviews for the two years following their release from prison in late 2007 and early 2008. For 18 of the interview subjects, we were able to compare self-reported residential histories from our own interviews for the first few months after release with those recorded in MDOC administrative data. Fourteen (78 percent) of these residential histories matched exactly, and the remaining four had one missing address each. Overall, 33 of 37 addresses were correctly recorded by MDOC parole agents. Missing addresses were either brief stays or short periods of living on the streets, and those with missing addresses tended to be more residentially mobile, suggesting that the administrative data will understate mobility slightly for some parolees. While two of the subjects experienced periods in which they were moving quickly between multiple addresses (staying with multiple friends or family members to avoid living on the streets or in a shelter), these periods were very short (only a few weeks).
Determining exact move-in and move-out dates for residences was particularly challenging. Approximately one quarter of the dates were estimated based on inexact information in the case notes. However, periods of absconding tend to be well documented in the case notes. Once a parole agent issues an absconding warrant, this signals that the parolee is no longer being supervised by the agent and so the agent cannot be held responsible for the parolee’s behavior.
Appendix Table A2 shows study period length by reason for the eventual end of the observation period.
For some subjects, multiple possible pre-prison addresses were identified in MDOC records. We used two methods to choose a single pre-prison address. Data used here prioritize identifying pre-prison addresses with community exposure and with a geocodable address. An alternative method, which produced almost identical results, prioritizes the most recent address. These methods resulted in different addresses for only three percent of individuals.
Tract characteristics for years between censuses were assigned values created by linear interpolation.
Distance between post-release and pre-prison address is undefined if either address is outside of Michigan, unknown, or is an address without community exposure. In addition, as time passes, some subjects become censored due to return to prison or discharge from parole. Appendix Table A3 contains information on undefined distances and their frequencies over time. An alternative way of comparing pre-prison and post-release addresses is exact address match. This comparison is contained in Appendix Table A4.
Appendix Table A5 examines variation in distance to pre-prison neighborhoods by demographic groups, as measured by the mean and median distance in miles between the address at each time point and the pre-prison address.
The subjects who were sent to probation detention centers were simultaneously under parole and probation supervision
We based this analysis on the 4,614 cases of intermediate sanctions where a parolee was living at a private address, experienced an intermediate sanction, and then moved back to a private address. In cases where an intermediate sanction was preceded or followed by another intermediate sanction or a period of absconding, we used the private residences most proximate in time to the sanction. We excluded cases where the parolee was returned to prison following an intermediate sanction without living in a private residence in between the sanction and prison.
Contributor Information
David J. Harding, Email: dharding@umich.edu.
Jeffrey D. Morenoff, Email: morenoff@umich.edu.
Claire W. Herbert, Email: clairewh@umich.edu.
References
- Alexander Michelle. The new Jim Crow: Mass incarceration in the age of colorblindness. New York: New Press; 2010. [Google Scholar]
- Binswanger Ingrid A, Stern Marc F, Deyo Richard A, Heagerty Patrick J, Cheadle Allen, Elmore Joann G, Koepsell Thomas D. Release from prison — A high risk of death for former inmates. New England Journal of Medicine. 2007;356:157–165. doi: 10.1056/NEJMsa064115. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Cadora Eric, Swartz Charles, Gordon Mannix. Criminal justice and health and human services: An exploration of overlapping needs, resources, and interests in Brooklyn neighborhoods. In: Travis Jeremy, Waul Michelle., editors. Prisoners Once Removed: The Impact of Incarceration and Reentry on Children, Families, and Communities. Washington, D.C.: The Urban Institute Press; 2003. [Google Scholar]
- Clear Todd. Imprisoning communities. New York: Oxford University Press; 2007. [Google Scholar]
- Clear Todd, Rose Dina, Waring Elin, Scully Kristen. Coercive mobility and crime: A preliminary examination of concentrated incarceration and social disorganization. Justice Quarterly. 2003;20(1):33–64. [Google Scholar]
- Columbia Spatial Information Design Lab. Million dollar blocks: Justice and the city. Columbia University Graduate School of Architecture, Planning and Preservation; 2006. Available from http://www.spatialinformationdesignlab.org/MEDIA/PDF_04.pdf. [Google Scholar]
- Ditton Paula M. Mental health and treatment of inmates and probationers (NCJ 174463) Washington, DC: U.S. Department of Justice, Bureau of Justice Statistics; 1999. [Google Scholar]
- Fagan Jeffrey, West Valerie, Holland Jan. Reciprocal effects of crime and incarceration in New York neighborhoods. Fordham Urban Law Journal. 2003;30:1551–1602. [Google Scholar]
- Garland David W., editor. Mass imprisonment: Social causes and consequences. New York: Sage; 2001. [Google Scholar]
- Geller Amanda, Curtis Marah A. A sort of homecoming: Incarceration and the housing security of urban men. Social Science Research. 2011;40:1196–1213. doi: 10.1016/j.ssresearch.2011.03.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Glaze Lauren E, Bonczar Thomas F. Bureau of Justice Statistics Bulletin. Washington, DC: U.S. Government Printing Office; 2011. Probation and parole in the United States, 2010. [Google Scholar]
- Groves Robert M, Jr, Fowler Floyd J, Couper Mick P, Lepkowski James M, Singer Eleanor, Tourangeau Roger. Survey methodology. Hoboken, New Jersey: Wiley; 2004. [Google Scholar]
- Jacqueline Helfgott. Ex-offender needs versus community opportunity in Seattle, Washington. Probation. 1997;8:12–24. [Google Scholar]
- Hipp John R, Yates Daniel K. Do returning parolees affect neighborhood crime? A case study of Sacramento. Criminology. 2009;47(3):619–656. [Google Scholar]
- Hipp John R, Petersilia Joan, Turner Susan. Parolee recidivism in California: The effect of neighborhood context and social service agency characteristics. Criminology. 2010;48(4):947–979. [Google Scholar]
- Holzer Harry J. What Employers Want: Job Prospects for Less-Educated Workers. New York: Russell Sage Foundation; 1996. [Google Scholar]
- Holzer Harry J, Offner Paul, Sorensen Elaine. What explains the continuing decline in labor force activity among young black men? Labor History. 2005;46:37–55. [Google Scholar]
- Hughes Timothy A, Wilson Doris James, Beck Allen J. Bureau of Justice Statistics. Special Report (NCJ 184735) Washington, DC: U.S. Department of Justice, Bureau of Justice Statistics; 2001. Trends in state parole, 1990–2000. [Google Scholar]
- Kirk David S. A natural experiment on residential change and recidivism: Lessons from Hurricane Katrina. American Sociological Review. 2009;74:484–505. [Google Scholar]
- Kubrin Charis E, Stewart Eric A. Predicting who reoffends: The neglected role of neighborhood context in recidivism studies. Criminology. 2006;44(1):165–197. [Google Scholar]
- La Vigne Nancy, Parthasarathy Barbara. Prisoner Reentry and Residential Mobility. Washington, D.C.: Justice Policy Center, Urban Institute; 2005. [Google Scholar]
- Lynch James P, Sabol William J. Effects of incarceration on informal social control. In: Pattillo Mary, Weiman David, Western Bruce., editors. Imprisoning America: The social effects of mass incarceration. New York: Russell Sage Founcation; 2004. [Google Scholar]
- Mauer Marc. Race to incarcerate. New York: New Press; 1999. [Google Scholar]
- Mears Daniel P, Wang Xia, Hay Carter, Bales William D. Social ecology and recidivism: Implications for prisoner reentry. Criminology. 2008;46(2):301–340. [Google Scholar]
- Metraux Stephen, Culhane Dennis P. Homeless Shelter Use and Reincarceration Following Release. Criminology and Public Policy. 2004;3:139–160. [Google Scholar]
- Metraux Stephen, Roman Caterina G, Cho Richard S. National Symposium on Homelessness Research. Washington, DC: US Department of Housing and Urban Development; 2007. Incarceration and homelessness. [Google Scholar]
- National Research Council. Washington, D.C.: The National Academies Press; 2007. Parole, desistance from crime, and community integration. [Google Scholar]
- Pager Devah. The mark of a criminal record. American Journal of Sociology. 2003;108(5):937–975. [Google Scholar]
- Petersilia Joan. When prisoners come home: Parole and prisoner reentry. New York: Oxford University Press; 2003. [Google Scholar]
- Pew Center on the States. One in 31: The long reach of American corrections. Washington, DC: The Pew Charitable Trusts; 2009. Mar, 2009. [Google Scholar]
- Roman Caterina G, Travis Jeremy. Where will I sleep tomorrow? Housing, homelessness, and the returning prisoner. Housing Policy Debate. 2006;17:389–418. [Google Scholar]
- Sampson Robert J, Loeffler Charles. Punishment's place: the local concentration of mass incarceration. Daedalus. 2010;139(3):20–31. doi: 10.1162/daed_a_00020. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Schnittker Jason, John Andrea. Enduring stigma: The long-term effects of incarceration on health. Journal of Health and Social Behavior. 2007;48(2):115–130. doi: 10.1177/002214650704800202. [DOI] [PubMed] [Google Scholar]
- Solomon Amy L, Thomson Gillian L. Prisoner Reentry in Michigan. Washington, DC: Urban Institute Justice Policy Center; 2004. [Google Scholar]
- Sourcebook of Criminal Justice Statistics Online. Table 6.0018.2006: Parolees Returned to Incarceration. 2011. Available from http://www.albany.edu/sourcebook/pdf/t600182006.pdf. [Google Scholar]
- Taxman Faye S, Young Douglas W, Wiersema Brian, Rhodes Anne, Mitchell Suzanne. The national criminal justice treatment practices survey: Multilevel survey methods and procedures. Journal of Substance Abuse Treatment. 2007;32(3):225–238. doi: 10.1016/j.jsat.2007.01.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- U.S. Department of Housing and Urban Development. ‘One strike and you're out’ screening and eviction policies for public housing authorities (HAs) 1996 PIH 96-16(HA), Issued April 12, 1996.
- Visher Christy A, Travis Jeremy. "Transitions from prison to community: Understanding individual pathways. Annual Review of Sociology. 2003;29:89–113. [Google Scholar]
- Wacquant Loïc. Deadly symbiosis: When ghetto and prison meet and mesh. Punishment & Society. 2001;3:95–134. [Google Scholar]
- Western Bruce. Punishment and inequality in America. New York: Russell Sage; 2006. [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.