Staff As a Conduit for Contraband: Developing and Testing Key Assumptions of Professional Boundary Violations in Prison

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Accepted preprint to: Peterson, B. E., & Kim, K. (2024). Staff As a Conduit for Contraband: Developing and
Testing Key Assumptions of Professional Boundary Violations in Prison. Deviant Behavior.
1
Staff as a Conduit for Contraband: Developing and Testing Key
Assumptions of Professional Boundary Violations in Prison
Authors
Bryce E Peterson1 ORCID: 0000-0003-1303-2696
KiDeuk Kim1
1 Center for Justice Research and Innovation, CAN Corporation
2 Justice Policy Center, Urban Institute
Corresponding author
Bryce E. Peterson, petersonb@cna.org, (703) 824-2476
CNA Corporation, 3003 Washington Boulevard, Arlington, VA 22201-2194
Acknowledgements
This work was supported in part by the National Institute of Justice [grant number 2015-IJ-
CX-K001]. The opinions, findings, and conclusions or recommendations expressed in this
publication are those of the authors and do not necessarily reflect those of the Department of
Justice.
Declarations of interest statement
The authors have no conflicts of interest to report associated with this project.

Accepted preprint to: Peterson, B. E., & Kim, K. (2024). Staff As a Conduit for Contraband: Developing and
Testing Key Assumptions of Professional Boundary Violations in Prison. Deviant Behavior.
2
Staff as a Conduit for Contraband: Developing and Testing Key
Assumptions of Professional Boundary Violations in Prison
Abstract
The breach of professional boundaries by correctional staff involves various
transgressive behaviors and improper relationships with incarcerated individuals.
Extant literature has focused on identifying and measuring such behaviors using non-
probability samples of correctional officers and formerly incarcerated individuals from
single jurisdictions. This research aims to build on this body of work by exploring how
key measures related to a specific type boundary violations – staff involvement in
introducing contraband – affects the level of contraband in 301 prisons across six states.
We investigate three key assumptions about staff motivations for smuggling contraband
into their facilities. Some motivations, such as (1) inappropriate relationships with
residents and (2) financial gains, tend to be premediated while others, like (3) the lack
of accountability and oversight at work, can create opportunistic circumstances that
affect staff motivations. The results from negative binomial regression show modest
support for each assumption tested in explaining the levels of contraband drugs and
cellphones while accounting for relevant prison characteristics. We conclude by delving
into the implications of our findings for research, policy, and practice.
Keywords
Boundary violations, prison, staff, contraband
Introduction
The US system of corrections is complex, comprised of thousands of distinct, yet
interdependent agencies with carceral responsibilities (Clear et al. 2012). This includes 50
state prison systems (typically called “departments of corrections”) and the federal Bureau of
Prisons who are responsible for the confinement of more than 1.4 million people convicted of
crimes and serving longer sentences, as well as nearly 3,000 city and county agencies that
hold around 730,000 individuals in jail awaiting trial or serving short sentences for minor
criminal convictions (Dholakia 2023; Kluckow and Zeng 2022). Across these various
agencies, there were an estimated 363,250 individuals serving as correctional officers or
jailers in the United States in 2022 (Bureau of Labor Statistics 2023). These security
personnel are accompanied by hundreds of thousands of additional non-security staff (e.g.,
therapists, counselors, case managers, etc.) who provide services and other supports to
incarcerated people and the operations of the facility (Clear et al. 2012).
The primary charge of prisons and jail employees, particularly correctional officers, is
to manage people in custody and maintain institutional order (Bottoms 1999; Cressey 1959).
However, some staff members engage in deviant behaviors that directly undermine this
mission. For example, there is a lengthy body of literature on prison staff “boundary
violations,” which refer to the transgressions or breaches of professional boundaries. Past
research has explored instances where prison staff commit physical or sexual assault against
incarcerated individuals, neglect their medical needs, allow them to fight with or assault one
another, bring contraband into the facility, or otherwise engage in inappropriate behaviors

Accepted preprint to: Peterson, B. E., & Kim, K. (2024). Staff As a Conduit for Contraband: Developing and
Testing Key Assumptions of Professional Boundary Violations in Prison. Deviant Behavior.
3
and relationships with the people they are charged with managing (Allen and Bosta 1981;
Blackburn et al. 2011; Dial and Worley 2008; Marquart, Barnhill, and Balshaw-Biddle 2001;
Novisky, Narvey, and Piquero 2022; Peterson et al. 2023; Worley 2011; Worley and
Cheeseman 2006; Worley and Worley 2011; Worley, Marquart, and Mullings 2003; Worley,
Tewksbury, and Frantzen 2010; Worley, Worley, and Hsu 2018).
A recent scoping review identified 20 peer reviewed studies published in the last two
decades that measured boundary violative behaviors in prison (Kelly and Potter 2023). The
samples from all but one of these studies were drawn from US prisons. The review indicates
that past research has predominantly examined staff boundary violations within a single
jurisdiction, relying on non-probabilistic samples. Through surveys, interviews, and focus
groups with correctional staff and incarcerated individuals, prior research has established
several explanations for why staff engage in various boundary violative behaviors. However,
a shortcoming of this scholarship arises from the limited applicability inherent in single-
jurisdiction studies. Moreover, while extant scholarship has measured self-reported
perceptions and experiences with boundary violations, it has not yet examined how
established boundary violation mechanisms are associated with critical measures of
institutional safety and security.
We aim to address these limitations and enhance existing knowledge by focusing on a
specific aspect of boundary violations – contraband introduction – using prison-level data
from six states. Drawing upon extant scholarship, we argue that (a) correctional staff are
responsible for a large portion of contraband introduction and (b) there are established
mechanisms related to boundary violations (i.e., inappropriate relationships, low pay, and
limited accountability) that can help explain these behaviors. We draw upon this literature to
develop and test a model of prison-level factors to assess which facilities are “at risk” for
contraband. Though this study is exploratory in nature, we believe it yields information that
is of both theoretical and practical relevance.
Correctional Contraband
Correctional contraband includes any material that is prohibited by a prison or jail’s
administration (Kalinich and Stojkovic 1985). Peterson and colleagues (2023) further
distinguish between items made by modifying materials found inside the facility, such as
weapons, and items that must be smuggled into prison from the outside, which include drugs
and cellphones. The latter category is most relevant for the study of staff boundary violations
(Novisky, Narvey, and Piquero 2022). These items also pose significant risks to institutional
security and the safety of staff and incarcerated residents.
For example, drugs have become a regular and important part of the lives of
incarcerated individuals (Bucerius, Haggerty, and Berardi 2023). A study of US prison
systems found that there were nearly 30 drug recoveries per 1,000 incarcerated individuals
each year, which is likely a substantial undercount (Peterson et al. 2023). In the UK, Bell and
Leese (2020) estimated that drug use is around nine times higher among people in prison than
those in the community. Because of their value and illicit nature, drugs create unregulated
prison economies that lead to unmonitored transactions, debts between incarcerated
individuals, and power struggles between gangs and other social groups inside and outside
the prison (Centre for Social Justice 2015; Lankenau 2001; Maitra 2023; Pyrooz and Decker
2019). Incarcerated residents who participate in these economies are at a significantly greater
risk of violent victimization (Copes et al. 2010). Moreover, drug use in prison has significant

Accepted preprint to: Peterson, B. E., & Kim, K. (2024). Staff As a Conduit for Contraband: Developing and
Testing Key Assumptions of Professional Boundary Violations in Prison. Deviant Behavior.
4
public health effects, including the development or sustainment of substance use problems,
overdoes, and the spread of HIV (Anderson et al. 2023; Centre for Social Justice, 2015;
Dillon 2001; Scott et al. 2021; Swann and James 1998).
Contraband cellphones likewise pose a significant risk to prisons. A recent survey
found that 25,840 cellphones were recovered in one year across 20 state correctional systems
(Shukla, Peterson, and Kim 2024). These devices are used by incarcerated people to organize
a range of criminal activities inside (riots, escapes, assaults, contraband smuggling) and
outside (drug trafficking, homicide, bribes, fraud, extortion, witness intimidation, harassment,
child pornography) the facility (Burke and Owen 2010; National Institute of Justice 2023;
Russo et al. 2022; Wiltz 2016). Analysis of contraband cellphone usage patterns by
Grommon and colleagues (2016) confirms that, while incarcerated people use these devices
to communicate with family members and friends and engage in other everyday activities,
they are also used to facilitate criminal enterprise. Incarcerated and formerly incarcerated
individuals have similarly reported using cellphones for both normal and nefarious purposes,
such as viewing pornography, accessing social media, and smuggling and paying for
contraband (Dittmann 2015; O’Hagan and Hardwick 2017).
Given the detrimental consequences of contraband items like drugs and cellphones for
the wellness of people in prison, it is critical to understand how these items get into the
institution and how officials find and remove them. Because there are thousands of different
correctional agencies in the US and, there is no single “business as usual” when it comes to
contraband entry points or interdiction strategies. Yet, there are some general findings that
emerge from the literature. For instance, Peterson and colleagues (2023) found that,
according to prison administrators, problematic entry points for contraband include staff,
visitors, mail, incarcerated individuals returning to the facility, and items being thrown or
flown over the perimeter. Not surprisingly, then, agencies implement a variety of
technologies and non-technological strategies to prevent the introduction of these items.
While some of strategies are less common (e.g., digitizing inmate mail, drone detection, RF
detection, whole body scanners), most prisons employ metal detectors, surveillance cameras,
pat and strip searches, cell shakedowns, searches of staff and visitors’ personal items, staff-
initiated investigations, and canines trained to detect contraband (Criminal Justice Testing
and Evaluation Consortium 2022; Peterson et al. 2023; Russo et al. 2021; Shukla, Peterson,
and Kim 2024). Based on case studies of one prison and two jail systems in the US, the
typical interdiction process includes processing mail through x-ray machines, running every
person (visitor, staff member, and resident) entering the facility through a metal detector or
body scanner, regularly patrolling the perimeters of facilities, and conducting both targeted
and random cell searches and shakedowns (Shukla, Peterson, and Kim 2021).
While contraband gets into facilities through a variety of means, staff are clearly an
important part of this process. For example, one study found that, across 150 prisons, there
were more staff violations per year on average (2.57) than visitor violations (1.68) (Peterson
et al. 2023). Another survey of 15 states reported a combined total of 2,352 administrative
sanctions for staff, 478 staff terminations, and 207 staff arrests over a one-year period
(Shukla, Peterson, and Kim 2024). Yet, while we know that staff play a central role in the
introduction of several types of contraband, the literature falls short in explaining the
motivations behind such behaviors. For that, we turn to the boundary violations literature.
Prison Boundary Violations

Accepted preprint to: Peterson, B. E., & Kim, K. (2024). Staff As a Conduit for Contraband: Developing and
Testing Key Assumptions of Professional Boundary Violations in Prison. Deviant Behavior.
5
Some of the earliest correctional scholarship centered on how social control in prisons
can be achieved through informal, reciprocal staff-resident relationships and correctional
officers’ enforcement of rules and regulations (Clemmer 1940; Cloward 1960; Cressey 1959;
Sykes 1958). This concept has been re-examined in the years since, with numerous studies
from the US and abroad offering support and clarifications of these original assumptions (see
Crewe, Goldsmith, and Hasley 2022). Liebling (2011) contends that the moral and relational
climate within prisons, including the expression of authority by staff, are foundational to
residents’ adjustment and the efficacy of institutional order (see also Crewe, Liebling, and
Hulley 2011). Yet the need for both cooperation and compromise between correctional staff
and incarcerated residents makes correctional corruption “an inevitable part of the
configurations of power… in most correctional settings” (Goldsmith, Halsey, and de Vel-
Palumbo 2018: 1). That is, rather than adhering to clearly delineated lines between “inmate”
and “employee” (Higgins, Smith, and Swartz 2022), some staff engage in boundary
violations when they “blur, minimize, or disrupt the professional distance’’ between
themselves and the incarcerated people they serve (Marquart, Barnhill, and Balshaw-Biddle
2001: 878).
Prison environments may be particularly conducive to staff corruption and boundary
violations because of the frequent contact, forced sharing of spaces, and extreme power
dynamics between staff and incarcerated residents (Cooke et al. 2019). Gooch (2022) also
argues that an increase in deprivations related to material goods and services over the past
decade has allowed illicit prison economies, which are essential for the spread of contraband,
to persist and flourish. This has resulted in a range of unprofessional and unethical boundary
violative behaviors, which have been categorized as deviance against the institution, deviance
against the incarcerated population, or deviance against other staff (Ross 2013).
A recent scoping review on boundary violations examined 20 peer reviewed studies.
The authors identified common themes in this work, which included the measurement of
boundary violative behaviors, the individual or environmental characteristics that lead to such
behaviors, and recommendations for reducing staff violations (Kelly and Potter 2023). Most
studies relied on interviews, surveys, and focus groups with prison staff (e.g., Lambert,
Worley, and Worley 2018; Marquart, Barnhill, and Balshaw-Biddle 2001; Worley, Worley,
and Lambert 2021; Worley and Worley 2011, 2016) or (formerly) incarcerated individuals
(e.g., Blackburn et al. 2011; Calhoun and Coleman 2002; Dial and Worley 2008; Kubiak,
Hanna, and Balton 2005; Novisky, Narvey, and Piquero 2022; Worley 2011; Worley and
Cheeseman 2006; Worley, Marquart, and Mullings 2003; Worley, Tewksbury, and Frantzen
2010; Worley, Worley, and Hsu 2018).
In applying this literature to the current study, we have identified three primary
assumptions about why staff might introduce contraband into correctional institutions. We
describe these three assumptions in the following section and, in doing so, argue that current
research has begun to establish an empirical and theoretical link between these underlying
mechanisms and staff decisions to engage in contraband-related boundary violations. We
then use these assumptions to inform development of our study’s independent variables.
Assumptions Relevant to Staff Contraband Introduction
Assumption 1: Staff may bring contraband into prison because of inappropriate
relationships with incarcerated residents, particularly between female staff and male
residents. Every instance of boundary violations related to contraband involves inappropriate
relationships or interactions between prison staff and incarcerated residents. However, the

Accepted preprint to: Peterson, B. E., & Kim, K. (2024). Staff As a Conduit for Contraband: Developing and
Testing Key Assumptions of Professional Boundary Violations in Prison. Deviant Behavior.
6
literature offers a more nuanced, and gendered, explanation for these relationships. For
example, when in the context of male staff working in female prisons, most researchers and
policymakers focus on the power dynamics, coercion, and potential for sexual abuse
(Calhoun and Coleman 2002). Blackburn and colleagues (2011) note that incarcerated
women face continued subordination and sexual exploitation, exacerbating feelings of
powerlessness. In these circumstances, there is less incentive for male staff to introduce
contraband, other than as a step towards engaging in sexual misconduct (Novisky, Narvey,
and Piquero 2022).
Staff-resident relationships involving sexual coercion and exploitation commonly
depict “male correctional officers preying upon female inmates” (Worley, Worley, and Hsu
2018: 333). Yet, the dynamics shift when considering female staff in male prisons. The
literature tends to portray incarcerated men as the predators looking to form exploitive
relationships with female staff. For example, Allen and Bosta (1981) first introduced the
concept of “turners”, incarcerated residents who establish relationships with staff members to
manipulate them into violative behaviors. Turners observe and initiate conversations with
staff, targeting those who exhibit social isolation, relationship and family issues, wild social
lives, drug or financial problems, and job-related stress (Salter 2018; Worley, Marquart, and
Mullings 2003). Women are often seen as more susceptible to flattery or intimidation, which
increases their likelihood of being “turned” or victimized by incarcerated men (Dial and
Worley 2008; Worley and Cheeseman 2006). Marquart, Barnhill, and Balshaw-Biddle’s
(2001) analysis of 549 correctional employee personnel files found that most boundary
violators were women in male institutions who had sexual relations with residents.
In such relationships, there is typically a quid pro quo dynamic in which residents
coerce staff members into providing favors or goods in exchange for their romance and
companionship (Cooke et al. 2019). Thus, one might reasonably anticipate that male facilities
with a higher proportion of female staff would present more opportunities for boundary
violations, leading to higher levels of contraband, compared to those with a lower proportion
of female staff.
Assumption 2: Staff bring contraband into prison to supplement their income. In
some cases, staff may introduce contraband into facilities because of the perceived financial
gain. A long-held axiom among correctional employees is that they are underpaid and
underappreciated (Cooke et al. 2019). Perceptions of inadequate pay, particularly as it
compares to similarly demanding jobs, is a significant source of stress among correctional
officers (Schaufeli and Peeters 2000). Correctional officers with more concerns about their
pay also have significantly reduced job satisfaction (Worley, Lambert, and Worley 2019).
Thus, low pay, especially among frontline officers and other lower-level employees, can
create an incentive for staff to seek additional sources of income like trading in contraband
items (Riley 2017; Souryal 2009). Worley and Cheeseman (2006) noted that financial
problems among correctional staff are a “non-shareable problem” that may make them more
susceptible to be manipulated into boundary violative behavior.
Even previously incarcerated individuals have asserted that staff pay is a likely
contributor to employees’ decision to bring contraband into the facility (Dittmann 2019;
Novisky, Narvey, and Piquero 2022). Drawing from interviews of 30 formerly incarcerated
gang members in the New England area of the US, Ortiz (2018) offers a description of the
“greasy” correctional officer, who is an active participant in the prison black market and
engages in a mutually beneficial relationship with prison gang members. As one of the
interviewees described:

Accepted preprint to: Peterson, B. E., & Kim, K. (2024). Staff As a Conduit for Contraband: Developing and
Testing Key Assumptions of Professional Boundary Violations in Prison. Deviant Behavior.
7
[There are] greasy-ass officers who if you do something for them, they’ll do
something for you. You’ve got your officers who bring their work here… CO’s bring
in phones, let drugs in…. They getting paid off of it. They getting paid top dollar. The
money is in the prison. There is no one on the street making money like someone in
the prison is making money. (Ortiz 2018: 111).
Worley and Worley further develop and examine the “economics of crossing over”
hypothesis, positing that “correctional officers who perceive themselves to be undervalued
and unappreciated feel closer to those relatively further deprived than themselves, in this
case, the inmates, because it alleviates their lowly status and boosts their confidence (2016:
26). In their survey analysis of 501 correctional officers, the authors found that job pay was
significantly, negatively related to self-reported boundary violations. In other words, the
poorer the perceived pay, the more likely officers were to engage in or have attitudes
favorable to boundary violations (Worley and Worley 2016). In short, prior literature has
established a link between an officer’s salary and the decision to engage in boundary
violations. Extending this, because we know staff are a significant source of contraband, one
would expect prison wages to be directly, inversely correlated with the amount of highly
valued illicit items (such as drugs and cellphones) in the facility.
Assumption 3: Understaffed facilities with limited accountability create
opportunities in which staff may feel incentivized to smuggle contraband into prison.
A commonly held opinion among correctional administrators and policymakers is that
adequate staffing levels can improve safety within prisons. Specifically, “an institution that is
staffed with more correctional officers relative to its inmate population may be less likely to
have higher levels of violence because more of the actual inmate deviance may be detected”
(Steiner 2009: 140). Poor staffing levels can also increase the use of overtime among
correctional officers, making them less alert and creating additional safety issues (Trautman
2022). Thus, staff may be more emboldened to introduce contraband into facilities that are
understaffed with limited or otherwise attenuated accountability from peers and leadership.
Supporting this notion, Kelly and Potter’s scoping review (2023) notes that boundary
violations were more prevalent in prisons that had staffing shortages and higher resident-
officer ratios. In addition to deterring violations, higher staffing levels can bolster informal
mechanisms of social control. Staffing shortages increase workload demands and job stress,
which then disrupt the social bonds among correctional officers that protect against
widespread violative behavior (Worley, Worley, and Hsu 2018; see also Calhoun and
Coleman 2002). Taylor-McCune (2020) specifically notes that such conditions affect staff
morale and feelings of institutional support, increasing the likelihood of contraband
introduction.
Thus, it is reasonable to expect that having lower relative staffing levels would create
more opportunities for the introduction of contraband, including by staff via reduced peer
accountability and social control. A recent study offers direct support of this assumption,
finding a positive relationship between the resident-to-officer ratio of a facility and
contraband levels. The authors argued that in facilities with lower staffing levels, officers had
a more difficult time effectively monitoring residents and preventing contraband introduction
(Peterson, Kim, and Shukla, 2024).
Current Study

Accepted preprint to: Peterson, B. E., & Kim, K. (2024). Staff As a Conduit for Contraband: Developing and
Testing Key Assumptions of Professional Boundary Violations in Prison. Deviant Behavior.
8
There are two relevant takeaways from the literature that provide a foundation for the
current study. First, staff play a central role in how contraband, particularly high-value items
like drugs and cellphones, gets into correctional institutions. Second, the boundary violations
literature offers three assumptions about why staff might engage in this behavior, including
inappropriate relationships with incarcerated residents, low pay, and reduced accountability.
Current research substantiating these assumptions indicates that they can explain attitudes
toward boundary violations and self-reported violative behaviors. This paper builds on this
scholarship by developing a model to test whether these three mechanisms are also associated
with a prison's reported contraband levels.
This study, and the variables described below, are not meant to serve as direct
measures of boundary violations. Rather, our goal is to determine whether organizational
dynamics that may influence a staff member’s decision to engage in boundary violations can
help explain facility-level variation in critical measures of institutional safety and security.
Given this approach, we caution that this study should be viewed as exploratory, though we
hope to generate knowledge of theoretical and practical relevance and establish a framework
for future research.
Data
We use data from the National Survey of Correctional Contraband (NSCC) (Peterson
and Kim 2018). The goals of the NSCC were to estimate the prevalence and types of
contraband known to prison administrators, determine the methods by which contraband is
introduced to these facilities, quantify the occurrence of contraband-related violence and
misconduct, and understand the implementation of various interdiction strategies. To develop
the survey, the NSCC research team conducted interviews and focus groups with both
correctional administrators and formerly incarcerated individuals to ensure the survey items
were valid and meaningful. They also received input on the survey instrument from
professional correctional organizations like the American Correctional Association,
American Jail Association, Correctional Leaders Association, and National Institute of
Corrections. The researchers then piloted the NSCC in nine facilities and solicited feedback
on survey language, data viability, and accessibility. They incorporated this feedback into the
final survey instrument (Peterson, Kim, and Shukla 2024).
Once finalized, the NSCC team sent the survey to nine state departments of
corrections and asked them to provide a response for every adult prison in their jurisdiction,
including those operated by the agency and those operated by a private corporation on behalf
of the agency. Three agencies declined or were unable to participate in survey, resulting in a
response rate of 67% (6 of 9 departments of corrections) and a final analytic sample of 301
prisons across the 6 participating states (Arkansas, Florida, Oregon, Tennessee, Texas, and
Wyoming). The NSCC survey instrument asked respondents to provide data related to
contraband recoveries, prison staff, incarcerated residents, contraband interdiction strategies,
and facility characteristics and programs (for more information, see Peterson et al. 2023;
Peterson, Kim, and Shukla 2024).
Study Measures
Dependent variables: NSCC respondents reported the number and type of
contraband recoveries that occurred in their facilities between January 1 and December 31,
2018. The survey defined recoveries as any incident where staff found or recovered
contraband items, regardless of whether an individual was disciplined for the associated
infraction. In addition, the survey asked respondents to count each type of recovered item

Accepted preprint to: Peterson, B. E., & Kim, K. (2024). Staff As a Conduit for Contraband: Developing and
Testing Key Assumptions of Professional Boundary Violations in Prison. Deviant Behavior.
9
separately. For example, if someone recovered a cellphone and a container of drugs during
the same incident, these would be separately reported in the NSCC. Given our focus on staff
contraband introduction, we defined two primary outcomes for this study: total drug
recoveries and total cellphone recoveries. We elected not to examine other types of
contraband recoveries available in the NSCC (e.g., weapons, alcohol, modified property,
excessive property), since these would disproportionately be made from items already located
in the prison and not brought into the facility by staff or another external individual. For
example, most contraband weapons are manufactured from items found inside the facility
(e.g., a toothbrush or piece of metal); it is much less common for incarcerated individuals to
smuggle a pre-made knife or other weapon into the facility from outside. Likewise, alcohol is
typically made inside the facility using fruit and other available ingredients, not smuggled
into the facility from the outside (Shukla, Peterson, and Kim 2021).
Independent variables: To develop measures related to the boundary violation
assumptions described above, we created seven independent variables from the NSCC data.
To investigate the first assumption about inappropriate relationships between staff and
residents, we measure the percent female staff in NSCC prisons. This is the percentage of all
staff (including security and non-security staff) that were reported to be female. According to
the literature, women are more likely to be “turned” to become boundary violators (Dial and
Worley 2008; Marquart, Barnhill, and Balshaw-Biddle 2001; Worley and Cheeseman 2006).
However, because the literature also focuses on incarcerated men as the “tuners”, we also
created a variable interacting the percent female staff with male prisons. Including both these
variables provides us with a more nuanced understanding of the impact of having a female
prison workforce on contraband levels.
To test the second assumption that staff smuggle contraband into prison to
supplement their income, we created two complementary measures. First, we used data from
the 2019 Bureau of Labor Statistics (BLS) to determine the average annual salary for state
correctional employees.
1
Second, prior research suggests that how correctional officers’ pay
compares to other jobs may be a more meaningful measure than their absolute salary
(Schaufeli and Peeters 2000). We therefore combined BLS data with the Census Bureau’s
American Community Survey 2018 5-year data to create a measure of employees’ relative
salary, which was the average annual correctional employee salary minus the median income
of the county in which the prison was located (i.e., positive numbers indicate that correctional
employees made more, on average, than the county median). These variables allow us to
estimate the impact of overall correctional employee pay, as well as their relative pay, on
prison contraband levels.
For the final assumption that contraband is a product of staffing shortages and limited
accountability, we created three measures. The first measure, resident-officer ratio, is the
facility’s average daily population (ADP) divided by its total number of security staff
1
We used the statewide average salaries for North American Industry Classification System (NAICS) code
92214: Correctional Institutions in the 2019 BLS data. While BJS provides some county-level salary
information under this code, it was not available for most counties in which NSCC facilities were located. It is
also worth noting that, though state departments of corrections may adjust staff salaries slightly to account for
cost-of-living differences between counties, there was very little variation between county-level and statewide
salaries in the BLS data. Thus, we used statewide data as the measure of staff salaries.

Accepted preprint to: Peterson, B. E., & Kim, K. (2024). Staff As a Conduit for Contraband: Developing and
Testing Key Assumptions of Professional Boundary Violations in Prison. Deviant Behavior.
10
(defined as correctional officers of all ranks). However, we do not assume that the
relationship between resident-officer ratio and contraband recoveries is linear. While having
too few officers might create more opportunities for staff to bring contraband into prison, at a
certain point there might be too few officers to actively search for and recover contraband.
We thus created a quadradic term (i.e., resident-officer ratio2), to test if it this measure has a
curvilinear relationship with contraband recoveries.
To further examine the concept of accountability, we created a measure of the number
of interdiction interventions targeting staff. The NSCC asked respondents to indicate which
of the following 12 contraband interdiction strategies they used on either security or non-
security personnel: walk-through metal detectors, x-ray, body scanner, regular pat searches,
random pat search, random drug test, statewide contraband interdiction team, contraband
interdiction team at facility, K9 unit, surveillance cameras, mass spectrometry, and staff-
initiated investigation and intelligence. This variable is an additive scale with a maximum
total value of 24 (i.e., 12 possible interventions for security staff + 12 for non-security staff).
Larger values thus indicate facilities employed a more comprehensive approach to staff
contraband interdiction (i.e., higher accountability).
In addition to these primary independent variables, we included several additional
facility-level controls that were likely to be related to contraband levels. These include the
area, indicating whether the prison was in a rural (reference category), suburban, or urban
area. Private facility indicates whether the facility was operated by a private contractor
instead of a government agency. Security level indicates whether the prison was given a
security classification of minimum/low (reference category), medium, maximum/high, or
other (e.g., administrative facilities with no specific classification level and facilities with
multiple classification levels). Campus design indicates whether the architectural design of
the prison is made up of several buildings spread across a large area, like a campus (with
other types of designs serving as a reference, including radial, telephone pole, and courtyard
prisons). Facility size is a measure of the facility’s rated capacity, categorized into small
(capacity under 500; reference category), medium (capacity between 500 and 1,000), large
(capacity between 1,000 and 2,000), and mega (capacity over 2,000). Percent capacity is the
ADP divided by the rated capacity. Outside work indicates whether the facility had residents
who provided work outside the facility, such as on cleanup crews or other public maintenance
work. Work release program indicates whether the facility allowed individuals to be in the
community unsupervised for a work release, educational release, or treatment release
program. Contact visit indicates whether all residents in the prison were allowed contact
visits. Finally, male facility indicates whether the facility held only male residents (with
female facilities serving as the reference category).
Analytic Approach
Our two outcome variables – drugs and cellphones– are count variables indicating the
number of recovered contraband items over the one-year study period. As is typical with
these types of variables, both outcomes were highly skewed (i.e., a higher number of “0”,
“1”, and other low values). It would therefore not be appropriate to use linear regression for
these analyses and we instead considered Poisson and negative binomial models. We found
that our data were overdispersed (i.e., the variance in the outcome variables was greater than
their mean), indicating that the negative binomial distribution was a better fit for our data
than the Poisson distribution (Long and Freese 2006). Like all count models, negative
binomial analyses allow for the inclusion of an exposure variable. This accounts for
differential exposures in each observation to the potential outcome. For example, the number

Accepted preprint to: Peterson, B. E., & Kim, K. (2024). Staff As a Conduit for Contraband: Developing and
Testing Key Assumptions of Professional Boundary Violations in Prison. Deviant Behavior.
11
of contraband recoveries in a prison would certainly be associated with the number of people
in that facility. We thus included ADP as an exposure variable in our models, which
transform our outcomes into a rate of contraband recoveries per incarcerated resident. We
also include state-level fixed effects in all our models to control for unobserved differences
within NSCC agencies. We used STATA version 18 for our analyses.
We report the incidence rate ratios (IRRs) for each independent variable in our
models. IRRs are easier to interpret than the unstandardized coefficients produced by default
in count models. As an example, if male prisons recovered contraband drugs at a rate of 10
per 100 residents and female prisons recovered contraband drugs at a rate of 5 per 100
residents, the IRR would be 10/5 = 2.0. This would indicate that male prisons recovered
twice as much contraband drugs as, or had a recovery rate twice that of, female prisons.
However, if the opposite was true and male prisons had 5 drug recoveries and female prisons
had 10 drug recoveries, the IRR would be 5/10 = 0.5. In this case, male prisons would have a
drug recovery rate that is half that of female prisons. For each outcome, we report two
models. The first includes all covariates other than the male facility-female staff interaction
effect and resident-staff ratio quadratic term, while the second is the full model. This allows
us to identify the baseline effect of our main variables, as well as the moderating effects of
the interaction and quadradic terms.
Results
Table 1 presents the descriptive statistics of the dependent and independent variables
included in the analytic models. On average, prisons who participated in the NSCC reported
28 drug recoveries and 31 cellphone recoveries over the one-year study period. Based on the
facility-level control variables included in the models, most prisons (72.4%) were in
rural/frontier areas, with much fewer in suburban (16%) or urban (11.6%) areas. Just over 7%
of the prisons were privately operated. Approximately half were classified as maximum or
high security, one-fourth classified as minimum or low security, while the remainder were
classified as either medium security (15.7%) or other (6.7%). Two-thirds of the prisons had a
campus design and they ranged in size from small (31.6%), medium (19.6%), large (35.9%),
and mega (13%). The average prison participating in the NSCC was under-capacity (92%).
Although relatively few prisons permitted residents to participate in outside work programs
(38%) or work release programs (14%), most provided all their residents with contact
visitation (72%). Nearly 85% of the prisons held males, while the remaining held females.
In terms of our staff boundary violation measures, we found that, on average, 42% of
the prison staff were females. One male-only prison employed zero women, while all other
prisons had a workforce comprised of at least 15 percent female employes. Our estimate
appears to be higher than national averages. Recent data from the Bureau of Justice Statistics
(BJS) reports that, across all US prison systems, only 26.3% of security staff are female, with
a higher percentage of women in female-only prisons (51.6%) than male-only prisons
(24.4%) (Maruschak and Buehler, 2021). Still, the two measures are not directly comparable:
The BJS estimate includes only security staff while our measure combines security and non-
security staff.
In our sample, correctional employees made an average of $48,521.97 per year, which
ranged from $28,367 to $95,561. This is similar to national estimates, which place the
median salary for correctional officers and jailers at $49,610 (Bureau of Labor Statistics
2023). On average, officers’ salary was $4,613.03 less than the median income of the county

Accepted preprint to: Peterson, B. E., & Kim, K. (2024). Staff As a Conduit for Contraband: Developing and
Testing Key Assumptions of Professional Boundary Violations in Prison. Deviant Behavior.
12
in which the prison was located, though the relative salary also varied between $50,511 under
to $37,789 over the county median. There were just under 6 residents per officer across these
prisons, slightly more than the 5 to 1 national average for state prisons (Maruschak and
Buehler, 2021). Finally, prisons in our sample implemented approximately 14 different
contraband interdiction strategies targeting prison employees, reflecting the varied nature of
agencies’ approach to combatting contraband (see Peterson et al. 2023).
Table 1. Descriptive Statistics of (n=301)
Mean/Percent
Std. Dev.
Min-Max
Dependent variables
Drug recoveries
28.46
40.05
0 - 269
Cellphone recoveries
30.97
53.73
0 - 366
Boundary violation variables
Percent female staff
42.45
12.82
0 - 100
Annual correctional employee salary
$48,521.97
$10,836.31
$28,367 - $95,561
Relative salary
-$4,613.04
$12,110.01
-$50,511 - $37,789
Resident-officer ratio
5.94
1.87
0.57 - 15.49
# of staff interventions
13.70
3.73
0 - 22
Other covariates
Area
Rural/frontiera
72.4%
-
-
Suburban
16.0%
-
-
Urban
11.6%
-
-
Private facility
7.4%
-
-
Security level
Minimum/lowa
25.8%
-
-
Medium
15.7%
-
-
Maximum/high
51.8%
-
-
Other
6.7%
-
-
Campus design
65.8%
Facility size
Smalla
31.6%
-
-
Medium
19.6%
-
-
Large
35.9%
-
-
Mega
13.0%
-
-
Percent capacity
91.71
13.32
17.71 - 137.5
Outside work
37.9%
-
-
Work release program
14.3%
-
-
Contact visit
72.1%
-
-
Male facility
84.4%
-
-
a Reference category in the analytic models
Contraband Drugs
The results from the negative binomial regression models examining contraband
drugs are reported in Table 2. There were a few significant relationships between the staff
boundary violation variables and contraband drug recoveries. Notably, in model 1, the
percentage of female staff in a facility reduced drugs in prison such that every percentage
point increase in female staff resulted in 2% fewer drugs recovered over the one-year study
period (IRR = 0.98, p < .01). This difference is no longer significant in Model 2 when the

Accepted preprint to: Peterson, B. E., & Kim, K. (2024). Staff As a Conduit for Contraband: Developing and
Testing Key Assumptions of Professional Boundary Violations in Prison. Deviant Behavior.
13
interaction between female staff and male prisons is included, though the interaction term is
also insignificant.
The effect of salary across both models suggests that prisons with higher staff salaries
have fewer drugs. Note that the actual IRR was 0.999887 (model 1; p <.01). While this seems
to be a small effective size, it is important to remember that the IRR indicates how a one-unit
change in the independent variable (a $1.00 increase of salary) relates to a unit change in the
outcome (number of contraband drugs recovered). To put that in more meaningful numbers,
we found that a $10,000 increase in employee salaries is associated with 1.1 fewer drug
recoveries. We also found no relationship between relative salary (the difference between
officer’s salary and the surrounding area’s median income) and contraband drugs.
Table 2. Results of negative binomial regression models (contraband drugs)
Model 1
Model 2
IRR
SE
IRR
SE
Boundary violation variables
Percent female staff
0.98
0.007 **
0.98
0.015
Salary
0.99 1
0.000 **
0.99 1
0.000 **
Relative salary
0.99 1
0.000
0.99 1
0.000
Resident-officer ratio
1.10
0.051 *
1.46
0.201 **
# of staff interventions
1.06
0.022 **
1.06
0.022 **
Male facility × female staff
0.99
0.017
Resident-officer ratio2
0.98
0.009 *
Other covariates
Area: Suburban
0.61
0.116 **
0.63
0.123 *
Area: Urban
0.88
0.175
0.92
0.182
Private facility
0.99
0.386
1.41
0.607
Security: Medium
1.23
0.289
1.24
0.288
Security: Maximum
1.52
0.347 †
1.58
0.359 *
Security: Other
1.38
0.423
1.52
0.470
Campus design
1.00
0.155
0.99
0.154
Size: Medium
0.69
0.152 †
0.74
0.162
Size: Large
0.89
0.180
0.90
0.180
Size: Mega
1.33
0.402
1.38
0.410
Percent capacity
1.00
0.005
1.00
0.005
Outside work
1.09
0.195
1.13
0.200
Work release program
0.69
0.140 †
0.70
0.142 †
Contact visit
0.92
0.129
0.91
0.127
Male facility
1.31
0.253
1.81
1.385
Observations
287
287
Likelihood Ratio χ2
232.77 ***
237.41 ***
Pseudo R2
0.101
0.103
1 If rounded, this value is “1.00” but is presented as “0.99” to show directionality of the relationship.
IRR incidence rate ratio, SE standard errors.
Models include ADP as exposure variable and state-level controls.
Bolding indicates statistical significance.
† p < .10, * p < .05, ** p < .01

Accepted preprint to: Peterson, B. E., & Kim, K. (2024). Staff As a Conduit for Contraband: Developing and
Testing Key Assumptions of Professional Boundary Violations in Prison. Deviant Behavior.
14
Finally, all measures of accountability were significant and in the expected direction.
In Model 1, we found that every one-unit increase in the number of residents per officer
resulted in a 10% increase in the recovery rate of contraband drugs (IRR = 1.10, p < .05).
However, in Model 2, the main effect becomes stronger (IRR = 1.46, p < .01) but the
quadradic term has the opposite effect (IRR = 0.98, p < .05). That is, we found that, overall,
higher resident-officer ratios increase contraband recoveries, but after a certain point this
relationship reverses, with contraband recoveries declining when there are too many residents
for staff members to supervise. We also found that the number of staff-focused interdiction
interventions was positively associated with contraband drugs such that each additional
intervention was associated with a 6% increase in the drug recovery rate (IRR = 1.06, p <
.01).
There were only two other covariates that were statistically significant in these
models. There were 37% fewer drug recoveries in prisons located in suburban areas
compared to those located in rural areas (IRR = 0.63, p < .05) and 58% more drug recoveries
in maximum security versus minimum security prisons (IRR = 1.58, p < .05).
Contraband Cellphones
Table 3 presents the results of the models examining contraband cellphone recoveries.
There are some similarities to the models examining drug recoveries, but several notable
differences, supporting our decision to separate these outcomes. Like the previous analyses,
the percentage of female staff reduced the drug recovery rate by approximately 3% (IRR =
0.97, p < .01). However, when the interaction term is included in model 2, the effect of this
variable is more than three times stronger, with drugs decreasing by 10% for every
percentage point increase in the share of female prison staff (IRR = 0.90, p < .01). Moreover,
the interaction term is also significant, but in the opposite direction (IRR = 1.09, p < .05).
That is, while female staff may decrease the number of contraband cellphones overall, they
are positively associated with cellphones in male-only prisons. This aligns with the
assumptions established in the boundary violations literature about the gender dynamics of
correctional employees and incarcerated residents.
In terms of the other variables of interest, we again found that salary was negatively
related to contraband cellphones levels and that it would take substantial increases in officer
pay to make modest reductions in the level of illicit cellphones (IRR = 0.999748, p <.01;
model 1). In other words, we would estimate that a $10,000 increase in employee salaries
would lead to 2.5 fewer cellphone recoveries. Results were similar for the measure of
relatively salary in Model 2 (IRR = 0.9999794, p <.05), indicating that how much staff make
relative to their county’s median income may also impact the number of phones in prison.
Notably, while the main effect of resident- officer ratio was insignificant in Model 1, Model 2
mirrors findings from our drug models. That is, the relationship between the main effect is
positive (IRR = 1.62, p < .05), while the impact of the quadradic term is negative (IRR =
0.97, p < .05). We also again found that each additional interdiction intervention targeting
staff increased the cellphone recovery rate by 9% (IRR = 1.09, p < .05).
There were five other covariates that statistically predicted cellphone recoveries. In
the first model, suburban prisons had around half the cellphones as those in rural areas (IRR
= 0.55, p < .05). Across both models, maximum security prisons (IRR = 3.20, p < .001) and
prisons with “other” security classifications (IRR = 4.34, p < .001) had cellphone recovery
rates that were three to four times higher than their minimum and low-security counterparts.
We also found that mega prisons had almost three times higher cellphone recovery rates as

Accepted preprint to: Peterson, B. E., & Kim, K. (2024). Staff As a Conduit for Contraband: Developing and
Testing Key Assumptions of Professional Boundary Violations in Prison. Deviant Behavior.
15
small prisons (IRR = 2.79, p < .001). It is important to note that this result controls for the
ADP and resident-officer ratio of these facilities, suggesting that the size of the prison, and
not merely the increase in the resident population, is important for understanding contraband
cellphone levels. Finally, in our first model, male facilities had nearly three times more
cellphones than female facilities (IRR = 2.77, p < .01), though this relationship was
attenuated when including the female staff-male prison interaction term in the second model.
Table 3. Results of negative binomial regression models (contraband cellphones)
Model 1
Model 2
IRR
SE
IRR
SE
Boundary violation variables
Percent female staff
0.97
0.010 **
0.90
0.031 **
Salary
0.99 1
0.000 **
1.00 1
0.000 ***
Relative salary
0.99 1
0.000 †
1.00 1
0.000 *
Resident-officer ratio
1.05
0.074
1.62
0.355 *
# of staff interventions
1.09
0.033 **
1.09
0.032 **
Male facility × female staff
1.09
0.038 *
Resident-officer ratio2
0.97
0.015 *
Other covariates
Area: Suburban
0.55
0.153 *
0.65
0.184
Area: Urban
0.94
0.284
1.05
0.312
Private facility
0.65
0.424
0.98
0.652
Security: Medium
1.33
0.452
1.40
0.463
Security: Maximum
3.20
1.002 ***
3.29
1.011 ***
Security: Other
4.34
1.819 ***
4.35
1.776 ***
Campus design
0.88
0.200
0.90
0.196
Size: Medium
0.82
0.261
0.86
0.272
Size: Large
0.90
0.252
0.83
0.230
Size: Mega
2.79
1.176 *
2.81
1.144 *
Percent capacity
1.00
0.008
1.19
0.317
Outside work
1.13
0.310
0.66
0.207
Work release program
0.73
0.229
0.96
0.184
Contact visit
0.96
0.190
0.07
0.110
Male facility
2.77
0.886 **
0.65
0.184 †
Observations
287
287
Likelihood Ratio χ2
235.47 ***
247.26 ***
Pseudo R2
0.112
0.118
1 If rounded, this value is “1.00” but is presented as “0.99” to show directionality of the relationship.
IRR incidence rate ratio, SE standard errors.
Models include ADP as exposure variable and state-level controls.
Bolding indicates statistical significance.
† p < .10, * p < .05, ** p < .01, *** p < .001
Discussion
This paper offers an exploratory analysis of how staff-related facility characteristics
may contribute to the overall levels of contraband in prisons. Though not a direct test of
boundary violations, our independent variables of interest were derived from three distinct

Accepted preprint to: Peterson, B. E., & Kim, K. (2024). Staff As a Conduit for Contraband: Developing and
Testing Key Assumptions of Professional Boundary Violations in Prison. Deviant Behavior.
16
assumptions about staff contraband introduction from the boundary violations literature. They
serve as proxy measures meant to estimate the degree to which these mechanisms can explain
why some prisons have higher levels of contraband than others.
We found modest, but mixed support for each of our measures. Prior literature
suggests that incarcerated men often serve as “turners” by preying on vulnerable female staff
to facilitate boundary violative relationships (Allen and Bosta 1981; Dial and Worley 2008;
Marquart, Barnhill, and Balshaw-Biddle; Salter 2018; Worley, Marquart, and Mullings 2003;
Worley and Cheeseman 2006). Given this, we expected that prisons with a greater share of
female employees would have relatively higher levels of contraband while controlling for
other covariates. However, our findings offer a more nuanced understanding of this
mechanism. First, taken as a whole, we found that the percentage of female staff was
negatively associated with contraband levels. That is, as the ratio of female officers to male
officers increases, the levels of reported drugs and cellphones would decrease. While this
finding seemingly contradicts our assumption about staff-resident relationships, it supports
other research on the potential efficacy of diversifying the prison workforce. For example,
prison reform advocates argue that women offer unique and complementary skills that can
improve correctional culture and enhance the management and care of incarcerated residents
(MTC Institute, 2008).
However, we also found that the interaction of female staff in male prisons may
increase illicit cellphones, though they have no impact on drugs. In other words, having
higher shares of female staff reduces overall levels of contraband cellphones and drugs across
facilities; but they may increase the number of cellphones (and not drugs) in male-only
prisons. Given that the interaction term was only significant in one of our models, we think
the overall protective factor of female staff against contraband, as described in the previous
paragraph, is of greater relevance to policy and practice. Still, future research should tease out
this finding and investigate how these gender dynamics affect other outcomes related to
boundary violative behaviors.
Research also indicates that staff compensation may be associated with contraband
introduction. In their test of the “economics of crossing over” hypothesis, Worley and Worley
(2016) found that poor pay was associated with favorable attitudes toward boundary
violations among correctional staff. We extended this concept by testing whether officers’
salary, and relative earnings, were associated with the amount of contraband in their prison.
We again found limited support for this assumption. Notably, employees’ relative salary (i.e.,
the difference between their annual earnings and the median income from the surrounding
county) had limited bearing on contraband levels (there was a significant relationship
between relative salary and contraband cellphones in one of the models). Conversely,
employees’ overall salary affected both contraband drugs and cellphones, although the
strength of these associations was relatively small. We estimated that increasing salaries by
$10,000 would yield a reduction in 1.1 drug and 2.5 cellphone recoveries per year. Given the
investment needed to make an appreciable impact on contraband levels, it is unclear how
much practical use this finding has to policymakers. Still, given the significance and direction
of our findings, this, too, should be explored further in future research.
Finally, we explored whether measures related to staffing levels and peer
accountability were associated with contraband. Our results yield interesting implications for
policy and research. Specifically, we found that the relationship between staffing and
contraband levels is not linear. Instead, we found that, overall, higher resident-staff ratios
increase the amount of contraband recovered in prisons, but that after a certain threshold,

Accepted preprint to: Peterson, B. E., & Kim, K. (2024). Staff As a Conduit for Contraband: Developing and
Testing Key Assumptions of Professional Boundary Violations in Prison. Deviant Behavior.
17
these ratios eventually decrease recoveries. One explanation for these findings is that staffing
shortages may increase workload demands and stress, which creates opportunities for staff
contraband introduction while also disrupting social ties that would otherwise make staff
more enthusiastic for their job and willing to hold each other accountable (Calhoun and
Coleman 2002; Kelly and Potter 2023; Worley, Worley, and Hsu 2018). At a certain point,
limitations in staff capacity become so severe that they neglect other critical functions of their
job, such as effectively searching for and recovering contraband items. In other words,
staffing levels may have a direct impact on contraband levels through increased opportunity,
as well as an indirect relationship through informal social control mechanisms. Future
research could examine facility-level measures of collective efficacy and perceptions of job-
related stress to determine whether these mediate the relationship between staffing and
contraband levels.
We also found that prisons with more interdiction interventions targeting staff
recovered more drugs and cellphones. At first, this appears to contradict our assumptions; one
might expect there to be less contraband in prisons employing more robust interdiction efforts
as these may effectively prevent and deter staff from bringing illicit items into the facility.
However, many of the strategies and technologies included in this measure (e.g., metal
detectors, body scanners, searches, mass spectrometry, and interdiction teams) were
specifically designed to detect both types of contraband as they are introduced into the
facility. Our findings, therefore, may show that facilities focused on finding contraband on
staff are successful, which then increases the rate of contraband recoveries in those facilities
(see also Clement, Kieckhaefer, and Marshall 2021).
Results from this study have several implications for policy and practice. One
recommendation from prior literature to mitigate staff boundary violations is to restrict cross-
sex staff deployments (Kelly and Potter 2023). We found some evidence that female staff in
male prisons increase certain types of contraband (e.g., cellphones); however, we also found
that female employees have a protective effect on overall contraband levels. Thus,
correctional administrators may consider recruiting and hiring more women. The California
Department of Corrections and Rehabilitation (CDCR), for example, recently launched an
initiative to increase recruitment, retention, and promotion of women, by identifying and
addressing barriers limiting female representation in the agency (CDCR 2023). Similar
efforts should be explored and replicated.
Still, given the potential for correctional employees, including women, to be targeted
by incarcerated “turners”, agencies should also deliver specialized training that helps officers
recognize and avoid such situations. Many agencies already provide some level of training
around sexual abuse prevention and resisting manipulation attempts by incarcerated
individuals. However, such trainings are often short and infrequent (Cooke et al. 2019).
These trainings could be expanded and modified to include gender-responsive elements.
Our findings underscore the importance of having adequately staffed facilities for
combatting contraband. This finding is especially critical in the wake of the COVID-19
pandemic, which has resulted in, among other issues, historic staffing shortages (Carson,
Nadel, and Gaes 2022; Felix et al. 2022). Addressing these shortages through improved
recruitment and retention efforts would therefore be an effective strategy for combatting
contraband – one that would enhance the safety and wellbeing of correctional staff and
incarcerated individuals.

Accepted preprint to: Peterson, B. E., & Kim, K. (2024). Staff As a Conduit for Contraband: Developing and
Testing Key Assumptions of Professional Boundary Violations in Prison. Deviant Behavior.
18
An oft-stated recommendation for minimizing boundary violations and reducing
prison contraband is to increase staff salaries (Riley 2017). Even formerly incarcerated
individuals have suggested that paying officers more would help prevent contraband from
getting into prisons (Dittmann 2019). Our findings indicate that correctional administrators
would need to increase employee salaries by tens of thousands of dollars to make meaningful
reductions in contraband. We understand that may not be feasible for many agencies.
However, it is possible that more modest salary adjustments, coupled with other targeted
interventions like staff training and better recruitment and retention, can be an effective
strategy for contraband interdiction.
Limitations
There are a few notable limitations in the current study that warrant discussion. First,
our independent variables are imperfect. “Boundary violations” are often viewed as and
studied with person-level dynamics. How an individual officer and a resident engage in an
improper relationship and how that relationship motivates the officer to bring in contraband.
Identifying and measuring these individual level mechanisms has been a focus of most prior
research, relying on interviews and surveys on the perceptions and experiences with
boundary violations from samples of correctional officers or formerly incarcerated
individuals. While these individual interactions provide more direct measures of boundary
violative behaviors, they are poorly suited for explaining at a macro-level which prisons are
most “at risk” for contraband. Therefore, rather than replicating prior research, our goal was
to develop and test measures related to organizational and prison-level dynamics. We do not
purport that these variables are direct measures of boundary violations but contend that they
are based on theoretically and empirically established assumptions about why staff would
engage in contraband introduction. Still, we recommend that future research consider ways to
measure staff-resident interactions more directly at the person-level or, at least, develop
facility-level measures more directly indicative of such violations, such as the number of
inappropriate liaisons in a facility.
We similarly acknowledge the limitations in our outcome variables (contraband drug
and cellphone recoveries). It is certainly true that the amount of contraband in a prison is a
product of an array of actors and actions independent of staff, including returning residents,
visitors, contractors, mail, drones and throwovers, etc. (see Peterson et al. 2023). It would be
misguided to assume that all recovered contraband items reported by prisons in the NSCC
facilities were smuggled in by staff. However, it is incontestable that staff are a significant
source of contraband, particularly for items that originate outside the facilities like drugs and
cellphones (Peterson et al. 2023; Shukla, Peterson, and Kim 2024). Thus, the extent to which
some prisons are more effective at preventing or dissuading staff from engaging in
contraband introduction, such as through higher salaries or having better staffing levels, one
would expect to observe at least some decline in contraband levels. In that vein, the purpose
of this study was to understand the extent to which our proxy measures of boundary violation
mechanisms can explain variation in contraband levels across prisons.
There are also inherent limitations in compiling contraband-related information (e.g.,
the number of recoveries) based on official reports. Not all illicit items in a prison will be
known, detected, or recovered, or even reported by staff. Similar to crime statistics, we
expect there to be a “dark figure” in official contraband records, with many items being
undetected and unreported (Bosma et al. 2020; Grommon, Carter, and Scheer 2018; Peterson,
Kim, and Shukla, 2024). It is also conceivable that the quality of reporting practices or
incident reports themselves may vary across the jurisdictions that participated in NSCC.

Accepted preprint to: Peterson, B. E., & Kim, K. (2024). Staff As a Conduit for Contraband: Developing and
Testing Key Assumptions of Professional Boundary Violations in Prison. Deviant Behavior.
19
Finally, the extent to which our findings can be generalized to broader settings is
unknown. The NSCC data are national in scope, representing six states of varying sizes.
Arguably, the NSCC data are more comprehensive and representative of contraband issues in
the US correctional population than other existing data sources available to date. However,
though the data show a substantial variation in key metrics, including the outcomes analyzed
in our study, they are limited to a sample of 301 prisons from 6 states. As noted throughout
this paper, prison systems vary substantially from each other, and certainly from local jails, in
terms of policies, procedures, and populations served. Moreover, how correctional staff may
engage in the smuggling of contraband, as a topic, is subject to quick judgment and public
censure. As such, it requires extra caution not to interpret our findings out of the context of
our analytic sample or beyond the setting used in our analysis.
Conclusion
Understanding the inner workings of a correctional facility has been of great interest
to a wide spectrum of individuals, ranging from scholars, policymakers, and commentators to
activists and various other stakeholders. However, it remains among the most underexplored
territories. Particularly, systematic information on correctional contraband, such as how much
contraband there is and how contraband is brought into a correctional facility, is extremely
rare even though such information holds immense relevance for the safety and wellbeing of
incarcerated individuals and correctional staff.
As such, it is crucial to recognize the need to be persistent and innovative in gathering
information on contraband, identifying knowledge gaps, and testing our assumptions, despite
inherent limitations and the gradual pace of such advancements. This exploratory study is
among the first systematic approaches to comprehending contraband issues and the ways in
which staff may be involved in its introduction. We strongly encourage future endeavors to
expand upon the analysis this study presents and improve upon its shortcomings.
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