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This is to certify that the

thesis entitled
CORRELATES OF INMATE VICTIMIZAUON

presented by

Charles L. Pratt

has been accepted towards fulﬁllment
of the requirements for

mpg—degree in Criminal Justice

 

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W Wan-p.14

CORRELATES OF INMATE VICTIMIZATION
By

Charles L. Pratt

A THESIS
Submitted to
Michigan State University
In partial fulﬁllment of the requirements
For the degree of
MASTER OF SCIENCE

School of Criminal Justice

1 999

ABSTRACT
CORRELATES OF INMATE VICTIMIZATION
By

Charles L. Pratt

Victimization of inmates is a serious concern for prison administrators. Every
year inmates are injured and killed while incarcerated. This study seeks to identify
factors associated with inmate victimization. It is hypothesized that contact with the
outside world by means of visits, letters, and phone calls will be inversely related to
victimization.

Data for this study were collected by surveying inmates from maximum and
medium security prisons throughout the United States. These data consist of several
individual-level characteristics.

The results of this study failed to support the hypotheses that continued contact
lessened the likelihood of victimization. The major ﬁnding in this study, however, was
that inmates who were involved in criminal activity while incarcerated were more likely

to be victimized than those inmates not involved in such activity.

TABLE OF CONTENTS

LIST OF TABLES .................................................................................. ii
INTRODUCTION ................................................................................... l
THEORETICAL FRAMEWORK ................................................................. 2
LITERATURE REVIEW ........................................................................... 5
RESEARCH OBJECTIVE ........................................................................ 10
DATA AND METHODS .......................................................................... ll
Dependent Variables ....................................................................... 13
Independent Variables ..................................................................... 15
Statistical Procedures ...................................................................... 18
ANALYSIS ........................................................................................... 18
DISCUSSION ........................................................................................ 28
NOTES ................................................................................................ 32
REFERENCES ...................................................................................... 33

LIST OF TABLES

Table 1 - Variable Coding and Descriptive Statistics .................................... 13
Table 1 - (cont’d) .............................................................................. 14
Table 1 - (cont’d) .............................................................................. 15
Table 2 - Bivariate Associations ............................................................. 19
Table 3 - Bivariate Associations ............................................................. 21
Table 4 - Multivariate Linear Regression Results for Victimization by Theft ......... 23
Table 5 - Multivariate Linear Regression Results for Victimization by Threats ...... 25
Table 6 - Multivariate Linear Regression Results for Victimization by Injury ........ 27

ii

INTRODUCTION

Who are the victims of crime behind prison walls? What factors are associated
with inmate victimization? These two questions are important given that victimization
rates are quite high in American prisons when compared to the general population
(Cooley, 1993; Maitland and Sluder, 1998). High rates of violence and victimization in
correctional institutions reﬂect poorly on the performance of prison administrators
(DiIulio, 1987). In addition, violence creates a more volatile environment where prison
staff carry out their responsibilities of managing the inmate population on a daily basis.

There is considerable extant research concerning crime inside American prisons.
Most research has been conducted using ofﬁcial prison records, and has focused on the
inmate offenders (Flanagan, 1983; Mabli, Holley, Patrick, and Walls, 1979; MacKenzie,
1987; Myers & Levy, 1978; Sorensen, Wrikle, and Gutierrez, 1998; Toch & Adams,
1986). This study breaks ﬁ'om such tradition, and instead focused on inmates who were
“victimized” inside maximum and medium security male prisons located throughout the
United States. In so doing, the factors associated with inmate victimization were
identiﬁed in an attempt to discover which are most salient.

The results ﬁom this research may help to generate much needed policy-oriented
knowledge. For example, the ﬁndings may prove useful to prison administrators in the
development and implementation of inmate classiﬁcation systems. Also, if the factors
that predict victimization can be identiﬁed, then these ﬁndings may be useﬁrl to prison
administrators in the development of programs to address speciﬁc problem areas within
their institutions. Third, if these results identify factors that reduce the probability of

victimization, then decision-makers may use such information in the development of

policies designed to reduce inmate victimization (e. g., contact with outside world).
Another possibility is that no signiﬁcant predictors will be identiﬁed. In this case the
results may inﬂuence decision-makers to reduce or eliminate costly programs based on
false assumptions about the correlates of victimization already in place or those being

considered for implementation.

THEORETICAL FRAMEWORK

Over the years researchers have developed two general models to explain the
inmate social system subcultures and assimilation process. These are referred to as the
“deprivation model” and the “importation model.” This review of the theoretical
literature will outline these two models.

The traditional view, which is commonly referred to as the “deprivation model,”
holds that norms, language, and social roles developed among inmates reﬂect the “pains”
associated with prison life (Clemmer, 1940; Sykes, 1958). These deprivations include
lack of freedom, emotional relationships with family and ﬁiends on the outside, material
goods and services, and heterosexual relationships. Other deprivations include the lack
of personal autonomy and lack of security (Sykes, 1958: 65-78).

The term “prisonization” has been used to identify the process by which new
inmates learn the norms and customs of prison society, what will be expected of them
while incarcerated, and the extent to which they internalize and act upon these norms.
The deprivation model holds that upon entry, inmates are stripped of their individual
identities, and subjected to a rigid, controlled environment where they must often learn to
fend for themselves. This process is believed to generate some degree of self-esteem

through resistance to, and manipulation of, the prison’s formal organizational structure

(Clemmer, 1940).

In contrast, the “importation model” maintains that the inmate social system
originates not so much ﬁ'om the prison environment, but rather from outside criminal
subcultures (Irwin and Cressey, 1962; Thomas, 1973; Thomas and Foster, 1973). The
importation model, which concedes that there is some inﬂuence of the deprivations
associated with incarceration, goes beyond the immediate situation and looks at pre-
prison factors, such as demographic characteristics and criminal history, to explain the
inmate social system. All inmates enter prison with a lifetime of experiences that have
shaped their personalities, and those experiences will determine how they react to life
behind bars. The importation model considers past life experiences and relationships and
the continuation of these relationships while incarcerated through contacts with those
outside prison walls. In addition, the importation model also considers the inmate’s
perception of hi s/her post-prison life opportunities to be important determinants of future
activities and associations (Sorensen et al., 1998; Thomas, 1973; Thomas and Foster,
1973)

Research has shown that continued contact with ﬁiends or family outside prison
may affect an inmate’s perception of his/her post-prison life opportunities (Grapendaal,
1990; Thomas, 1973, 1977; Thomas and Foster, 1973). Inmates who maintain contacts
with the outside world are more likely to have positive expectations of life after release
from prison. Positive post-prison expectations reduce the extent to which the inmate is
likely to become entrenched in the prison subculture, and thus reduces the likelihood of
involvement in criminal activity while incarcerated (Grapendaal, 1990; Thomas, 1973;

1977; Thomas and Foster, 1973).

For inmates with extensive involvement in criminal activity prior to incarceration,
continued contact with the criminal element outside prison while incarcerated may have a
negative effect. Grapendaal ( 1990) found that these inmates were more likely to exploit
their fellow inmates.

Some researchers have found evidence to suggest that the importation model
better explains prison violence (Cao et al., 1997; Harer and Steffensmeier, 1996; Irwin
and Cressey, 1962; Thomas, 1973; Thomas and Foster, 1973 ), while the work of others
supports the deprivation model (Clemmer, 1940; Fry and Frese, 1992; Sykes, 195 8).
More recently, this “either-or” approach has been abandoned and studies have sought to
integrate these two respective models (Grapendaal, 1990; Lawson, Segrin, and Ward,
1996; Sorensen et al., 1998). To date, existing studies have not focused on inmate
victimization per se, but rather on the assimilation processes associated with the adoption
of the inmate code. Even though these studies do not speciﬁcally address prison
violence, the theoretical frameworks driving them are applicable to the study of inmate
victimization given that violence and victimization are hypothesized to be adjustment
processes.

An inmate's activities and personal relationships are associated with the likelihood
of being victimized (Cohen, 1981; Felson, 1987; Wooldredge, 1998). At ﬁrst glance, this
appears to support the deprivation model. On the other hand, if it is true that past life
experiences inﬂuence these activities and relationships as implied by the importation
model, we must ask ourselves whether these two models are mutually exclusive. All
inmates suffer deprivations, however, not all inmates are victimized at the same rate

(Thomas, 1973). This indicates the presence of factors at work other than those imposed

by incarceration itself. These factors may very well include prior life experiences and
relationships, the continuation of these relationships while incarcerated, and the inmate’s
perception of his/her post-prison life opportunities. If these factors are associated with
the likelihood of becoming a victim of crime, then it follows that the importation model
may aid in predicting which inmate’s will most likely to be victimized. This study will
attempt to test the importation model as it applies to the association between prior life
experiences, existing personal relationships, and the continuation of such relationships

while incarcerated and inmates' likelihood of victimization.

LITERATURE REVIEW

Several researchers have sought to assess the impact of various factors
hypothesized to be associated with inmate victimization. As noted previously, most of
these studies have focused on the perpetrators of inmate violence (Flanagan, 1983;
McCorkle, Miethe, and Drass, 1995; Myers and Levy, 1978). In comparison, few studies
have been conducted that attempt to identify factors that would predict the likelihood of
an inmate being victimized during incarceration (Cooley, 1993; Wooldredge, 1994;
Wooldredge, 1998; Wright, 1991). This section consists of a review of the few existing
studies that have done so. In addition to identifying variables that have been used by
researchers in the past, the author will seek to identify additional factors that have not yet
been empirically assessed.

Dennis Cooley’s (1993) study of victimization in Canadian federal prisons
compared ofﬁcial victimization rates for the prisons studied to victimization rates
calculated from victim surveys completed in these prisons. These results indicate that

inmate victimization rates were nearly ﬁve times higher than the ofﬁcial victimization

rates published by the Canadian government (1). Cooley (1993) also compared
victimization rates for assault. He found that inmates were more frequently victims of
assault when compared to the general population (3 76 per 1,000 compared to 116 per
1,000). A sub-sample from the Canadian population consisting of urban males aged 20-
59 with annual income less than $20,000 was also compared to inmate victimization.
This comparison showed that approximately 60% more inmates were assaulted (3 76 per
1,000 compared to 227 per 1,000), but the number of assault incidents were actually
slightly higher in the sub-sample (417 per 1,000 compared to 402 per 1,000). Cooley
(1993) found that various factors, such as age, security level of the prison, and length of
time spent in the facility signiﬁcantly increased the odds of victimization. In other
words, victims tended to be younger, housed in maximum-security facilities, and in the
early stages of their sentence.

Wright (1991) argued that violence in prisons was not as prevalent ten or twenty
years ago as it is today due in part to informal control mechanisms. These controls
originated from an "inmate code discouraging exploitation of other inmates" (Wright,
1991z5). Informal social controls were commonly employed in the past. For example,
prison staff granted privileges to certain inmates in exchange for assistance in the
containment of disruptive behavior (Sykes, 1958). Wright (1991) suggests that recent
federal court decisions have limited this practice to the point of eliminating its
effectiveness (2).

In contrast to other studies (e.g., Lauritsen, Sampson and Laub, 1991), Wright
(1991) concluded that victims and their attackers were distinctive groups. He found that

violent inmates tended to be younger, unmanied, less educated, had a history of

unemployment prior to incarceration, had been involved in the criminal justice system at
an early age, and had prior institutional experience. Victims, on the other hand, tended to
have been less involved in crime prior to incarceration and were seldom charged with
aggressive behavior in prison, although the data indicated that they are more likely to
argue and ﬁght with inmates and staff. Wright (1991) hypothesized that argumentative
behavior may have been partly the cause of their victimization.

Wooldredge (1994) looked at pre-institutional variables and institutional variables
in an attempt to predict victimization and the perpetrators of crime in prison. Using
survey data from inmates housed in a medium security, adult male correctional facility
located in a Southwestern state, Wooldredge (1994) concluded that various inmate
characteristics (or pre-institutional variables) increased the likelihood of victimization.
According to Wooldredge (1994), Mexican-American inmates were more likely to be
victims of personal crimes than non-Mexican inmates. Further, younger inmates were
more likely to be victimized than older inmates were. Inmates with histories of prior
incarceration or commission of personal crime were also more likely to be victims of
personal crime. Wooldredge (1994) found that several institutional variables were also
important predictors of inmate victimization. For example, inmates who spent fewer
hours in recreational activity had fewer ﬁiends in the facility and did not receive monthly
visits ﬁ'om friends or families ﬁ'om outside the prison were also more likely to be victims
of personal crimes. Unfavorable attitudes toward the facility were also signiﬁcantly
related to personal crime victimization.

The list of signiﬁcant indicators of property crimes provided by Wooldredge

(1994) is much shorter than for personal crime. Mexican-American inmates were more

likely than non-Mexican and those inmates closer to the beginning of their sentence were
most likely to be victims of these types of crime (3).

An interesting aspect of Wooldredge's (1994) ﬁndings is that the factors common
among personal crime victims more than property crime victims, were associated more
with activities of the inmate-victim while at the facility. Hours of recreation, television,
number of ﬁiends at the facility, visits per month, are all signiﬁcant indicators of personal
crime. This combination of factors tend to support the lifestyle theory of inmate
victimization (Wooldedge, 1998), routine activities theory of crime victimization (F elson,
1987), and the criminal opportunity perspective (Cohen, 1981).

Wooldredge (1998) has also examined inmate lifestyles and their relationship to
victimization. The lifestyle theory asserts that people engage in vocational and leisure
activities that tend to increase or decrease their likelihood of being victimized through
their associations with potential offenders (see Hindelang, Gottfredson, and Garofalo,
1978). Wooldredge (1998) emphasized that all inmates are exposed to potential
offenders, however, some are more or less likely to be victimized because of the activities
they choose to be involved in or the type inmates they associate with. Inmates involved
in a greater amount of structured activities were less likely to be physically assaulted,
although this involvement showed a greater likelihood of victimization by theft. This
higher likelihood of theft is presumed to be the result of inmates being unable to
safeguard their property while at such activities. Several characteristics were correlated
with physical assault, including number of hours spent in recreational activities,
perceptions of alienation, visits, and income prior to incarceration. Age and number of

hours spent in educational activity were negatively correlated with physical assault at

signiﬁcant levels. Characteristics positively correlated with theft include prior felony
convictions, educational level, hours of vocational training and recreational activities (4).

Wooldredge (1998) concluded that his results validate the lifestyle theory of
crime victimization. These same results also validate the importation theory because
prior life experiences and relationships as well as demographic characteristics inﬂuence
what an inmate does in prison. This point is supported by Wooldredge’s (1998)
ﬁndings that demographic and background characteristics as a group predicted the
likelihood of physical assault.

In a study of victimization of younger inmates, Maitland and Sluder (1998) found
that white inmates were more likely to be victims of mind games, extortion of property,
physical injury and to have weapons used against them than non-whites (5). In general,
victims were less psychologically healthy, feared victimization more and found prison
more painful than non-victims. Conviction of violent crimes and amount of time spent in
correction institutions were not signiﬁcantly related to victimization. Age was not an
issue in this study because the prison under observation housed only young inmates. A
similar study of a facility housing a wider range of age groups may show age as a
signiﬁcant indicator of victimization. The size and design of the sample also present
external validity problems preventing generalization of the results to the general
population.

Previous research into inmate victimization has included such variables as age,
race, ethnicity, marital status and number of children, education, criminal and
incarceration history, and unemployment prior to incarceration. In addition, the amount

of time spent at work, counseling and recreational activities while incarcerated, the

number of ﬁiends within the prison, visits from friends and family members, and
inmates’ attitudes towards prison administration, programs and correctional officers are
included in various studies.

Some researchers have concluded that inmate victimization can best be explained
by the routine activities theory of criminal victimization (F elson, 1987) or the criminal
opportunities perspective (Cohen, 1981). These theories explain victimization based on
the assumption that victims and victimizers share common characteristics. Other
researchers reached the opposite conclusion (Wright, 1991), that victims and victimizers
are distinctive groups that share few, if any, characteristics.

Extant research, although sparse, has included many characteristics of inmate
crime victims. The current study attempted to include factors that were shown to be
signiﬁcant in past research, as well as add some other factors that may also increase the
likelihood of victimization. For example, this study included sexual orientation as a
control variable. It is possible that other inmates because of their sexual orientation may

target inmates who are not heterosexual as victims (6).

RESEARCH OBJECTIVE

This study attempted to test a set of hypotheses derived ﬁom the importation
model. Speciﬁcally, this study assessed the effects between prior life experiences,
personal relationships, and the continuation of such relationships while incarcerated on
the likelihood of victimization. To accomplish this task, “continued contact” with the
outside world will be measured using information concerning the number of visits,
number of personal letters received, and the number of phone calls made and received by

inmates. With this in mind, the following hypotheses will be tested:

10

Hypothesis 1: Continued contact with those outside prison is inversely

associated with victimization by serious threats of bodily injury.

Hypothesis 2: Continued contact with those outside prison is inversely

associated with victimization by assault resulting in injury.

H mothesis 3: Continued contact with those outside prison is inversely

associated with victimization by theft.

In addition to traditional hypothesis testing, this study also seeks to explore the
effects of other variables to determine which, if any, may be signiﬁcant predictors of
inmate victimization. Few studies have been conducted that have attempted to analyze
several individual characteristics of inmate-victims in an attempt to identify which were
signiﬁcant when controlling for many additional factors (W ooldredge, 1994, 1998).
Most studies have used only a small number of variables (Faulkner and Faulkner, 1997;
Flynn, 1992; Johnson and Lazarus, 1989), whereas this study includes many variables on
a wide range of t0pics. By doing so, this study seeks to advance our understanding of

criminal victimization inside the prison walls.

DATA AND METHODS

Data for the proposed study were provided by the Inter-University Consortium for
Political and Social Research at The University of Michigan. Data for the original study,
which was entitled "Inmate Victimization in State Prisons, 1979," were collected by Jan

E. Schreiber at the Social Science Research Institute under a grant from the National

11

Institute of Justice. The original study was conducted to determine the nature and extent
of victimization in state prisons located throughout the United States (Schreiber, 1983).

These data were collected by way of personal interviews with prison inmates in
maximum and medium security institutions over a six month period in 1979. The
institutions included in the sample were stratiﬁed by size and sex of inmate population,
and by region of the United States. This was done in order to include two large male
facilities (population over 500) and one small male facility (population under 500)
located throughout the country. From each facility, a maximum of 75 inmates were
randomly selected from the prison roster. There were 487 inmates in the original study
sample. Listwise deletion of missing data resulted in a sample of 323 inmates.

The more common method of data collection for this type of research has been
official prison records. The potential under-reporting of crime inside prisons as well as
the nature of some questions dealing with self-reporting of offenses committed by
inmates makes the personal interview an attractive alternative (Hewitt, Poole & Regoli,
1981). Although surveys do provide access to information not available through ofﬁcial
records, they are not infallible (Block and Block, 1984). Respondents may provide
inaccurate information. For example, participants may not remember incidents or dates
accurately. Another potential problem with obtaining information through the use of
inmate surveys is that respondents may fear reprisals from prison administration if they
give self-incriminating information. Questions of inmates remembering facts incorrectly
or intentionally misrepresenting facts in self-reports of criminal activity and victimization

may be an issue, although this type of data collection has become common in prison

12

studies in recent years (Cooley, 1993; Maitland and Sluder, 1998; Wooldredge 1994,

1993; Wright, 1991).

Dependent Variables

Dependent variables include speciﬁc types of inmate victimization. Three
dependent variables will be included: (1) the number of times the inmate has been a
victim of theft while incarcerated, censored with a ceiling of 40; (2) the number of times
the inmate has been subjected to serious threats of bodily injury while incarcerated,
censored with a ceiling of 32; and (3) the number of times the inmate has been a victim of
assault resulting in injury (7).

Table 1 includes a summary of descriptive statistics for all variables used for this

 

 

 

study.
Table 1
Variable Coding and Descriptive Statistics ’
Variable Description/Cmnes Values Mean SD
Independent Vambles
Visits # visits received per month 2.19 3.25
Letters # letters received per month 12.40 14.49
Phone calls # phone calls per month 3.59 7.06
Age Inmate age in years 27 .94 8.12
Race Caucasian O .46 .50
Non-Caucasian 1

Education Years of school completed 10.67 2.15
Mate income Income prior to incarcegtion 10,594.10 9646.42

 

13

Variable

Table] (cont’d)

 

 

DescriptionICat_egories Values hLean SD

Height Less than 5’8” 1 1.99 .64
Between 5’8” and 6’ 2
More than 6’ 3

Build Muscular 1 1 .73 .5 1
Average 2
F labby 3

Sexual orientation Heterosexual 0 .96 .19
Bisexual/homosexual 1

Prior convictions # prior felony convictions 1.07 1.56

Violent offense No 0 .55 .50
Yes 1

Life sentence No 0 .14 .35
Yes 1

Time incarcerated # months in current prison 19.14 20.17

Treatment # hours treatment per week 1.74 5.12

Work # hours worked per day 4.98 3.75

Recreation # hours recreational activity 10.04 11.71

Committed theft

in prison No 0 .06 .23
Yes 1

Made threats while

in prison No 0 .31 .46
Yes 1

Injured someone

while in prison No 0 .24 .43
Yes 1

Inmate friends # inmates as good friends 6.65 11.20

S_tajf friends # stﬁasgood ﬁienlds 1.89 4.21

 

 

l4

Table] (cont’d)

 

 

Variable Description/Categories Values Mean SD
Perceived personal
safety Very safe 1 2.43 .95
Fairly safe 2
Occasionally unsafe 3
Not safe at all 4
Perceived safety
of property Very safe 1 2.46 .98
Fairly safe 2
Occasionally unsafe 3
Not safe at all 4
Dependent Variables
Theft # times victimized by theﬁ 1.46 4.53
Threats # times seriously threatened 2. 16 6.33
Injured # times injured blassault .35 1.14

 

 

’ Descriptive statistics based on N = 323

Independent Variables

Several individual-level variables will be use. These independent variables
include many that have been used by other researchers in various studies, including
inmate demographic characteristics. Inmate contact with those outside the prison walls
is of primary interest in this study. Other studies have identiﬁed such continued contacts
as signiﬁcant determinants of victimization among prison inmates (Grapendaal, 1990;
Thomas, 1973; Thomas and Foster, 1973; Wooldredge, 1998). The number of visits an
inmate received per month, how many letters received per month, and how many phone
calls received or made by an inmate were used as indicators of contact with the outside.

Inmate age was measured in actual years as reported by the inmate respondent.

Race will be taken into account using a dummy variable: 0 = Caucasian and 1 = non-

15

Caucasian. The non-Caucasian category includes Black, Hispanic, Asian, Paciﬁc
Islander, Native American and Alaskan Indian inmates. Education will be included as a
control variable, and reﬂects the number of years of schooling completed. Inmate sexual
orientation is a dummy variable with O = heterosexual and l = bisexual or homosexual.
Height and build will be included as control variables to test for correlation between
physical prowess and victimization. Height is an ordered categorical variable: 1 = under
ﬁve feet eight inches tall, 2 = between ﬁve feet eight inches and six feet tall, and 3 = over
six feet tall. Build is coded similarly: 1 = muscular, 2 = average, and 3 = ﬂabby.

Wooldredge (1998) found income prior to incarceration to be a signiﬁcant
predictor of inmate victimization. This study included income prior to incarceration as
another control variable.

Self-reported criminal activity committed by inmates will also be included as a
series of dummy variables. More speciﬁcally, whether inmates committed theft while in
prison is coded: 0 = no and l = yes. Serious threats of bodily injury made by inmates
while incarcerated is coded: 0 = no and 1 = yes. The commission of assault resulting in
injury while in prison will be included as well, coded: 0 = no and l = yes.

Daily activities of inmates will also be included as statistical controls. The
number of hours inmates worked per day, the number of hours per week inmates were
involved in some sort of counseling or treatment, and the number of hours inmates were
involved in recreational activities per week, censored with a ceiling of 63 will be
included. The number of inmates considered to be good ﬁiends, censored with a ceiling
of 50, and the number of staff members considered to be good ﬁiends, censored with a

ceiling of 25 will also be included in the analysis.

16

Two variables will be included that measured inmates' perception of personal
safety within the prison as well as the safety of their property. Personal safety was
operationalized by the variable, "as far as being assaulted is concerned, does R think that
this prison is..." The response set to this statement included: 1 = very safe, 2 = fairly
safe, 3 = occasionally unsafe, and 4 = not safe at all. Safety of the inmates' property was
operationalized using the survey item: "Does R feel that R's property is...": 1 = very
safe, 2 = fairly safe, 3 = occasionally unsafe, and 4 = not safe at all. Although the means
and standard deviations for these two variables are quite similar, the correlation between
them (r = .19) does not necessitate combining these items into a composite variable.

Data related to the respondents' prison sentence and offense history is also
included as independent variables. Current conviction for violent offense was a dummy
variable: 0 = non-violent offense and 1 = violent offense. The violent offense category
includes the offenses of robbery, non-force sex offenses, forcible rape, ﬁrst and second
degree murder, murder, voluntary and involuntary manslaughter, manslaughter,
kidnapping, simple and aggravated assault, assault, attempted rape, attempted robbery,
attempted assault, attempted murder, accidental killing and killing in self-defense. The
non-violent reference category includes the offenses of burglary, larceny, motor vehicle
theft, receiving stolen goods, forgery, fraud, arson embezzlement, possession of drugs,

sale of drugs, narcotic offenses, prostitution, and commercial vice.
The amount of time respondents have spent in the current prison is recorded in
months with a censored ceiling of 131. Whether the inmate was serving a life sentence

will also be included as a dummy variable with O = no and 1 = yes. Prior felony

l7

convictions was operationalized as the number of times respondents reported that they

had been incarcerated in prison prior to the current sentence (8).

Statistical Procedures

The appropriate bivariate and multivariate statistical procedures to use with these
data are Pearson correlation coefﬁcient analysis and multivariate linear regression.
Multiple regression is useful for analysis when several control variables are included

(Bachman and Paternoster, 1997: 455, 489).

ANALYSIS

To examine the association between victimization and inmate characteristics a
correlation matrix was created. Relevant Pearson correlation coefficients from this
matrix are presented in Tables 2 and 3.

As Table 2 shows, there are no signiﬁcant relationships between any of the three
hypothesized victimization variables and visits, letters or phone calls. This lack of
relationships indicates that the hypotheses are not supported by the results of analysis.
There were however, some signiﬁcant relationships with the dependent variables.
Criminal activity while incarcerated is associated with each of the hypothesized
dependent variables. For victimization of theft, having committed theft (r = .14), having
made serious threats of violence (r = .12), and having committed assault resulting in
injury (r = .13) are signiﬁcant. For victimization of serious threats of violence, having
committed theft (r = .23), having made serious threats of violence (r = .30), and having
committed assault resulting in injury (r = .21) are all signiﬁcantly associated with one

another. Finally, victimization of assault resulting in injury is associated with having

18

Table 2

Bivariate Associationsa

 

 

Victim of theft Threatened Injured
Visits .070 -.081 .017
Letters .037 .016 .085
Phone calls .086 .067 .076
Age .076 -. 104 -.024
Race -. 143* -.079 -. 137*
Education -.047 -. 132* -.092
Inmate income .073 -.010 .094
Height -.03 1 -.039 -.027
Build -.044 .002 .042
Sexual orientation .009 -. 132* .060
Prior convictions -.028 .073 .004
Violent offense .023 .067 .051
Life sentence -.028 -.001 -.054
How long incarcerated .270" .073 .193”
Treatment .004 -.052 -.056
Work .014 .083 -.051
Recreation -.009 -.015 .020
Committed theft . 142* .226" .354"
Made threats .116* .304** .241 **
Injured someone .125* .213" .389"
Inmate ﬁiends .122* -.088 -.059
Staff friends .034 -.067 -.067
Perceived personal safety .096 .116* .177 **
Perceived safety of property .252" .125* .151*

 

’ Pearson correlation coefﬁcient
** Correlation signiﬁcant at .01
* Correlation signiﬁcant at .05

19

committed theft (r = .35), having made serious threats of violence (r = .24), and having
committed assault resulting in injury (r = .39) . These result would suggest that offenders
and their victims share common characteristics. The victims in this study have also been
offenders themselves.

Victimization of theft is associated with perception of safety of property (r = .25).
Victimization of serious threats of violence is associated with perception of personal
safety (r = .12), and perception of property safety (r = .13). Victimization of assault
resulting in injury is associated with perception of personal safety (r = .18), and
perception of safety of property (r = .15). These results suggest that an inmate who has
been victimized by any of the three offenses is likely to perceive a greater likelihood of
future victimization of both personal and property crime than an inmate who has not been
so victimized.

The length of time incarcerated in the current prison is signiﬁcantly associated
with two of the three hypothesized dependent variables. Victimization of theft (r = .27),
and victimization of assault resulting in injury (r = .19) are both signiﬁcantly associated
with the length of time incarcerated in the current prison. These results suggest that as
the length of incarceration increases, so does the likelihood of victimization.

Victimization of serious threats of violence and sexual orientation (r = -. l3), and
education (r = -.13) are also signiﬁcantly associated. These results would indicate that
less educated heterosexual inmates are more likely to be threatened with violence. Race
is also found signiﬁcantly associated with both victimization by theft (r = -. 14) and injury
by assault (r = -.14) indicating that Caucasian inmates are more likely to be victimized

than non-Caucasian inmates.

20

The number of inmate ﬁiends is signiﬁcantly associated with victimization by
theft (r = .12). This indicates that as the number of inmate fiiends increases so does the
likelihood of being victimized by theft. This suggests that the more trusting of other

inmates an inmate becomes, the more likely he/she is to be victimized.

 

 

Table 3
Bivariate Associationsa
Victim of theft Threatened Injured
Victim of theft 1.00
Threatened .21 * * l .00
Injured .38** .41** 1.00

 

’ Pearson correlation coefﬁcient
** Correlation signiﬁcant at .01
* Correlation signiﬁcant at .05

Table 3 presents signiﬁcant associations between the hypothesized dependent
variables. Victimization of theft is associated with having been victimized by serious
threats of violence (r = .21), and having been victimized by assault resulting in injury (r =
.38). Victimization of serious threats of violence is associated with having been
victimized by assault resulting in injury (r = .41). These results suggest that an inmate
victimized by any one of the three offenses studied is more likely to be victimized by one
or more of the other offenses than is an inmate who has not been victimized.

Pearson correlation coefﬁcients were estimated for all of the independent
variables in this analysis. None of these correlations, however were strong enough to

suggest that multicollinearity was a problem.

21

Analysis will be continued through the use of multivariate linear regression. The
analytic strategy was three pronged. First, the three dependent variables, number of times
victimized by theft, number of times victimized by serious threats of violence, and
number of times injured by assault were regressed onto the three independent variables,
number of visits, number of letters received, and number of phone calls made and
received (Model 1). Second, all dependent variables were regressed on the statistical
controls (Model 2). Finally, a ﬁll model, which included the theoretical variables of
interest and the statistical controls, was estimated (Model 3).

The results of these analyses, in the form of the standardized coefﬁcient (B), are
presented in Tables 4, 5 and 6. Table 4 presents the results for victimization by theft. In
Model 1 there are no signiﬁcant relationships among the hypothesized variables. This
fails to support the hypotheses that victimization by theft is inversely related to continued
contact with the outside world. Model 2 indicates signiﬁcant relationships for four of the
independent variables. More speciﬁcally: race (B = -.17, p<.01); length of time spent in
the current prison (B = .27, p<.001); perceived safety of property (B= .22, p<.001); and
the number of inmates considered as good friends (B = .11, p<.05) are all found to have
signiﬁcant relationships with victimization by theft. For model 3 the same four
signiﬁcant relationships are found: race (B = .18, p<.01); length of time spent in the
current prison (B = .26, p<.001); perceived safety of property (B = .22, p<.001): and the
number of inmates considered as good friends (B = .12, p<.05).

The results from table 4 suggest that Caucasian inmates are more likely to be
victimized by theft than non-Caucasians. Also, the longer an inmate is incarcerated the

greater the likelihood of being victimized by theft. As the number of inmates considered

22

Table 4

Multivariate Linear Regression Results for Victimization by Theft

 

Vagable Model 1 Model 2 Model 3
_B__ _l3_ _13_
Visits .08 .06
Letters -.03 -.01
Phone calls .09 .10
Age .02 .02
Race -.17** -.l8**
Education -.04 -.06
Inmate income .08 .06
Height .05 .04
Build -.06 -.06
Inmate sexual orientation .01 .02
Prior felony convictions -.05 -.03
Current conviction for violent offense -.01 .01
Life sentence -.11 -.11
How long incarcerated .27*** .26***
Treatment -.04 -.04
Work .00 .00
Recreation -.04 -.05
Has inmate committed theft in prison .10 .10
Has inmate made serious threats in prison .04 .04
Has inmate injured someone in prison -.05 -.06
Number of inmate ﬁiends .11* .12*
Number of staff friends .03 .01
Perceived personal safety .07 .09
Perceived safety of property .22*** .22***
1?.2 .02 .20 .21

 

* p<.05, ** p<.01, *** p<.001

23

as good friends increases, there also appears to be a slightly greater likelihood of
victimization of theft. Inmates who had been victimized by theft are less likely to
consider their property to be safe than ware those who have not been so victimized. A
very weak coefﬁcient of determination (R2) for Model 1 explains only approximately 2%
of the variance, while a moderate R2 for Model 2, which consisted of the statistical
controls, explains much more variation (20%). The full model, Model 3, explained 21%
of the variance.

Table 5 presents the results of analysis for victimization of serious threats of
violence. Model 1 again fails to support the hypotheses that visits, letters and phone calls
are inversely related to being threatened. No signiﬁcant relationships are found among
the hypothesized variables. There are however, three signiﬁcant relationships revealed in
Model 2. The number of hours an inmate worked (B = .11, p<.05), the inmate’s
commission of theft while incarcerated (B = .13, p<.05), and having made serious threats
of violence against someone while incarcerated (B = .19, p<.01) are all signiﬁcantly
related to receiving serious threats of injury. Model 3 contains the only signiﬁcant
relationship in this study for one of the hypothesized variables, this being the number of
phone calls received and made (B = .13, p<.05). The remaining signiﬁcant relationships
are with the same variables as model 2: The number of hours an inmate worked (B = .12,
p<.05); having committed theft while incarcerated (B = .12, p<.05); and having made
serious threats of violence against someone while incarcerated (B = .19, p<.01).

The results from table 5 suggest that inmates who have committed theft and made

serious threats of violence while incarcerated are more likely to receive serious threats of

24

Table 5

Multivariate Linear Regression Results for Victimization by Threats

 

Vagable Model 1 Model 2 Model 3
_B__ __.B__ _lt_
Visits -.05 -.09
Letters -.02 .02
Phone calls .07 .13“
Age -.08 -.09
Race -.06 -.08
Education -.07 -.07
Inmate income .01 .00
Height —.04 -.05
Build -.01 .00
Inmate sexual orientation -.10 -.09
Prior felony convictions .09 .10
Current conviction for violent offense .02 .03
Life sentence -.02 .00
How long incarcerated .02 .01
Treatment -.07 -.07
Work -.11* .12*
Recreation -.04 -.05
Has inmate committed theft in prison .13* .12*
Has inmate made serious threats in prison .19** .19**
Has inmate injured someone in prison .06 .06
Number of inmate friends -.05 -.04
Number of staff ﬁ'iends .01 .00
Perceived personal safety .08 .08
Perceived safety of property .08 .08
R2 .01 .18 .20

 

* p<.05, ** p<.01, *** p<.001

25

violence. Serious threats of violence also increase as inmates work more hours and talk
longer on the telephone. The coefﬁcient of determination (R2) for Model 1 is very weak
and explains only 1% of the variance. Model 2, which consists of the statistical controls,
explains 18% of the variance, while model 3, the full model explains 20% of the
variance.

Table 6 presents the results for victimization by assault resulting in injury. Once
again, none of the hypotheses are supported. No signiﬁcant relationships are found
among the hypothesized variables in Model 1. Model 2 reveals ﬁve signiﬁcant
relationships with injury by assault, including: Income prior to incarceration (B = .11,
p<.05); the commission of theft while incarcerated (B = .27, p<.001); having committed
assault resulting in injury (B = .25, p<.001); perceived personal safety (B = .13, p<.05);
and perceived safety of property (B = .10, p<.05). For model 3, there are also ﬁve
signiﬁcant relationships. Race is now signiﬁcant (B = -.11, p<.05), but inmate income is
not. The remaining four signiﬁcant relationships are the same as for model 2: The
commission of theft while incarcerated (B = .27, p<.001); having committed assault
resulting in injury (B = .24, p<.001); perceived personal safety (B = .13, p<.05); and
perceived safety of property (B = .10, p<.05).

Results from Table 6 suggest that inmates who have committed theft or assault
resulting in injury while incarcerated are more likely to be injured by assault. These are
some of the strongest relationships found in this study. Inmates who have been injured
by assault also have lower expectations of personal safety and to a lesser degree lower

expectations for the safety of their property. Caucasian inmates are slightly more likely

26

Table 6

Multivariate Linear Regression Results for Victimization by Injury

 

MUG Model 1 Model 2 Model 3
_B_ __B_ _B__
Visits .00 .00
Letters .08 .05
Phone calls .05 .10
Age -.01 -.01
Race -.10 -.11*
Education -.03 -.05
Inmate income .11* .10
Height .01 .00
Build .06 .06
Inmate sexual orientation .09 .10
Prior felony convictions -.01 .00
Current conviction for violent offense -.01 -.00
Life sentence -. 10 -.09
How long incarcerated .09 .09
Treatment -.04 -.04
Work -.02 -.02
Recreation -.02 -.03
Has inmate committed theft in prison .27*** .27***
Has inmate made serious threats in prison .02 .02
Has inmate injured someone in prison .25*** .24***
Number of inmate friends -.06 -.05
Number of staff ﬁiends .03 .01
Perceived personal safety .13* .13*
Perceived safety of property .10* .10*
R2 .01 .29 .31

 

* p<.05, ** p<.01, *** p<.001

27

to be injured by assault than non-Caucasian inmates and as inmate income prior to
incarceration increased, so does the incidents of injury by assault.
The coefﬁcient of determination (R2) for Model 1 is also very weak and only explains
1% of the variance, while the other two models in this table explain the highest
percentage of variation in this study. Model 2, the statistical controls model explains
29% of the variation, and model 3, the full model, explains approximately 31%.

There is only one signiﬁcant relationship among the three hypothesized
variables. The number of phone calls received and made is signiﬁcantly related to threats

of injury in the full model of Table 5.

DISCUSSION

The results from this analysis, as pointed out, did not support the three hypotheses
that inmates’ continued contact with the outside world by way of visits, letters and phone
calls reduces the likelihood of victimization inside prison. Support was also not found
for either the importation or deprivation models. Variables supporting both models were
included in the signiﬁcant as well as non-signiﬁcant categories. This failure to clearly
differentiate between deprivation and importation models supports the contention stated
in this study that these are not exclusive models.

There were, however, some results that stood out in regression analysis. Inmate
involvement in criminal activity while incarcerated appeared to be the most important
determinant of victimization involving serious threats of injury and injury by assault.
The commission of theft while incarcerated was signiﬁcantly related to both threats of

injury as well as injury by assault for both Models 2 and 3. Having made serious threats

28

of violence while incarcerated was signiﬁcantly related to receiving serious threats of
violence for Models 2 and 3. Commission of assault resulting in injury while
incarcerated was signiﬁcantly related to injury by assault for Models 2 and 3 as well.

Bivariate correlation results showed that the commission of all three offenses
studied, theft, threats or assault, were signiﬁcantly correlated with all three types of
victimization, theft, threats and injury by assault. These results appeared to support the
assumptions of the criminal victimization theory (F elson, 1987), the criminal
opportunities perspective (Cohen, 1981), and the lifestyle theory (W ooldredge, 1998) that
offenders and their victims shared common characteristics. It appears that for this sample
the same inmates were the victims and the victimizers. This is contrary to Wright’s
(1991) conclusion that victims and offenders are distinctive groups sharing few
characteristics.

Inmates that had been victims of theft, as well as injured by assault, were more
likely to be less secure in the safety of their property than those who had not been so
victimized. Inmates that had been injured by assault felt less secure ﬁ'om assault than did
non-victims. These results may very well have been caused by their victimization, but it
is also possible that these inmates were insecure about their safety prior to being
victimized, and this insecurity may have contributed to the victimization by making them
appear more vulnerable.

The results from the regression analysis suggest that Caucasians were more likely
to be victims of theft and to a lesser degree injury by assault than non-Caucasians.
Inmates that work longer hours were more likely to be threatened with violence. Inmates

that had higher income levels prior to incarceration appear to be injured by assault at a

29

higher rate. One result that was unexpected, is that inmates who had been incarcerated in
the current prison for a longer period of time had higher incidents of victimization by
theft and injury by assault. It is also curious that this study revealed no signiﬁcance
between age and victimization. Many studies have showed this to be a signiﬁcant
relationship (Cooley, 1993; Wooldredge, 1994, 1998).

The single signiﬁcant correlation among hypothesized variables is phone calls and
receiving serious threats of violence, this is a positive relationship, not negative as was
hypothesized.

Even though the hypothesized relationships were not supported, these ﬁndings
may be useﬁrl to prison decision-makers. The strongest relationships were found
between victimization by threats and injury and the commission of theft and assault. This
suggests for one thing, that inmates with a history of theft and assault are more likely to
be injured by assault, possibly out of revenge. Policies may be developed that place these
inmates in a more closely monitored section of a prison. By doing this, prison personnel
may reduce the likelihood of that inmate committing theft or assault as well as reducing
the likelihood of him/her being injured by assault resulting ﬁom revenge. The relatively
strong relationship between injury by assault and commission of assault resulting in
injury may also be of use to prison decision-makers. These results suggest that
victimizers are likely to become victims, possibly also motivated by revenge. Therefore,
inmates with histories of assaultive behavior are likely to be assaulted, perpetuating a
cycle of violence. Prison policy could be set to disperse these types of inmates among
the prison population. This would limit contact between assaultive inmates, hopefully

reducing the likelihood of confrontations. Results also reveal that Caucasian inmates are

30

more likely to be victimized by theft and to a lesser degree, injured by assault than non-
Caucasian inmates. The racial issue is always of concern for prison officials. With this
in mind, prison decision-makers need to address this potentially explosive issue. Policies
and directives need to be developed and enforced which attempt to eliminate any
preferential treatment of, as well as discrimination against any group by prison staff. If
inmates perceive racial discrimination from prison staff, this will escalate the problem.
Other measures could also be taken, such as race relation training, in an attempt to
eliminate racial discrimination.

The amount of research into inmate victimization has only begun to scratch the
surface of what needs to be done. This study and others like it have left many questions
unanswered as well as bringing up new questions regarding the victimization of prison
inmates. Signiﬁcant relationships that surface need further in-depth study. From the
results of this study, it appears that the inmate involvement in criminal activity while

incarcerated is a major area of concern that needs more study.

31

NOTES

1. Cooley (1993) randomly selected inmates who had served at least twelve
months in one of ﬁve federal prisons in Canada. The total number of cases is 117,
although only 97 were used in the analysis due to missing data,

2.Wright (1991) used ofﬁcial records and self-report surveys in this study. He
identiﬁed violent and victimized inmates ﬁ’om these sources. Data were collected from
ten male prisons in New York, ﬁve maximum security and ﬁve medium security. The
prisons were randomly selected. The total sample consisted of 942 inmates randomly
chosen from a list of inmates incarcerated in these facilities.

3. The prison in Wooldredge’s (1994) study housed such a low number of
Aﬁican-Americans that he did not include them as a category of race in his data analysis.

4. Wooldredge (1998) used surveys administered to inmates in three correctional
facilities. These included one medium and two high security facilities. Inmates were
chosen for the study by their respective wardens with a ﬁnal count of 58 1.

5. Maitland and Sluder (1998) sampled 111 inmates from a medium security,
male prison designed for 17-25 year old inmates. This prison had a population of
approximately 1,100 inmates. A non-probability sampling procedure was employed, and
111 inmate volunteer research subjects completed surveys.

6. Other factors, which may be signiﬁcant, include gang membership and
religious afﬁliation. These variables were not included in this study because this data
were not available in the data set used. More research is needed to assist in predicting
which inmates are most likely to be victimized.

7. Ceilings for the dependent variables in this study were set based on natural
breaks in groupings of occurrences. All ceilings were set above the 95th percentile. For
the number of times victimized by theft the 95 percentile was 5 and for the number of
times victimized by threats the 95th percentile was 10.

8. Ceilings for the independent variables in this study were set based on natural
Breaks in groupings of occurrences. All ceilings in this study were set above the 95‘h
percentile. For the number of hours involved in recreational activity per week the 95‘h
percentile was 39; for the number of inmates considered ﬁiends, the 95‘” percentile was
30; for the number of staff members, the 95‘h percentile was 9.6; for number of months
incarcerated in current prison, the 95th percentile was 61.8.

32

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35

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