Taking officer time seriously
| Date | 01 March 2018 |
| Published date | 01 March 2018 |
| Author | Brian Payne,Matthew DeMichele |
| DOI | 10.1177/0264550517748358 |
| Subject Matter | Articles |
Article
The Journal of Community and Criminal Justice
Probation Journal
Taking officer time
2018, Vol. 65(1) 39–60
ª The Author(s) 2017
seriously: A study
Reprints and permissions:
sagepub.co.uk/journalsPermissions.nav
DOI: 10.1177/0264550517748358
of the daily activities
journals.sagepub.com/home/prb
of probation officers
Matthew DeMichele
RTI International, North Carolina, USA
Brian Payne
Old Dominion University, Virginia, USA
Abstract
We use a time and motion study to understand how probation officers spend their
time. What officers spend their time doing and whom they spend their time with
demonstrates a deeper symbolic meaning of how the convicted should be treated,
what is believed effective to change behavior, and informs the community about
definitions of public safety. Explicitly studying officer time is a neglected area of
research. We model a count variable of minutes per task as a function of offender,
offense, and task characteristics using zero-truncated negative binomial regressions.
Results show that officers spend significantly more time with higher-risk offenders,
mixed results regarding domestic violence and sex offenders, and significantly less
time with older and black probationers. Our intentions are to delve deeper into how
officers spend their time to contribute to the development of an evidence-based model
of corrections.
Keywords
probation, workload, time study, organizational culture, managerialism, offender
management
Corresponding Author:
Matthew DeMichele, RTI International, Center for Justice, Safety and Resilience, 3040 Cornwallis Road,
Research Triangle Park, NC, USA.
Email: mdemichele@rti.org
40
Probation Journal 65(1)
Introduction
The US correctional system is grappling with several challenges related to the
growth in those under correctional supervision. Prisons and jails have grown from
the near-century-long average range of 125 to 150 per 100,000 incarcerated
adults to more than 700 inmates per 100,000 (Kaeble and Glaze, 2016; Garland,
2001). Incarceration has been linked to several long-lasting negative effects that
include diminished political rights (Uggen and Manza, 2002), lost employment
opportunities (Pager, 2007), and reduced quality of life (Comfort, 2005). Along-
side the growth in incarceration rates there has been a little noticed movement of
growth in community corrections populations as well (DeMichele, 2014; McNeill,
2013; Phelps, 2013).
Community supervision often is touted as a fix to the institutional corrections
overflow. Penal reformists suggest that placing individuals on probation or parole
is the solution to prison and jail overcrowding. For instance, the Pew Center On
the States, other policy associations, and the government have created many
opportunities for states to shift their emphasis away from incarceration toward
community punishments.1 However, what few people are discussing is the tenfold
growth in probation since the 1970s, when the Bureau of Justice Statistics started
collecting population data. In 1977 there were about 230 adults on probation for
every 100,000 in the population, and by 2015 this number had grown to nearly
1701 per 100,000 (Kaeble and Bonczar, 2016). This population growth,
especially alongside prison growth, poses unique policy challenges to scholars,
citizens, and governments.
This puts probation and parole in a difficult situation when staffing is low and
funding is limited. A central research gap in the evidence-based practices literature
is further understanding the activities officers regularly complete. How long do
officers spend on an office visit, visiting individuals in their homes or other settings,
or completing administrative functions? In this paper, we address this gap in
research by reporting the results from a time and motion analysis of two-dozen
county-level probation agencies.
First, we present the use of time and motion studies in community corrections.
Second, we review the methods used for conducting the time and motion study.
Third, we present descriptive statistics of the task analysis and results from a series of
truncated negative binomial regression models. The task analysis provides a
snapshot of the specific tasks and how long officers spend on those tasks, and the
regression models offer some understanding of the relationship between times spent
on tasks and offender demographics, risk levels, nature of the task, and type of
offense. The findings demonstrate that probation officers report spending nearly
equivalent amounts of time with probationers regardless of risk level. We identify a
set of limitations and weaknesses related to the study methodology, and suggest
policy implications that can reasonably be drawn from the findings. In the end,
we situate our study within the punishment and society literature to suggest that
probation agencies are organizational units that provide the rules and policies
that create shared meaning systems and action scripts that shape officers’ daily
DeMichele and Payne
41
activities. The tasks regularly completed by officers demonstrate how officers
translate organizational mandates into the everyday practice of probation. The
findings suggest that probation officers shape their daily activities to emphasize
face-to-face interactions with probationers. They may, however, have limited time to
engage individuals as much as they would prefer, but they appear to recognize the
need to interact with individuals.
It’s not about numbers. It’s about what officers do
Community supervision administrators grapple with complex issues to ensure that
offenders are supervised at required levels. Can they hire new staff if some staff
leaves? What sorts of tasks are contracted versus completed internally? Offenders’
needs and risks are highly variable, with some offenders having substance abuse
problems, others having trouble locating and remaining employed, and others with
various mental health conditions. Making situations more complicated is the fact
that many offenders have various combinations of such problems. The compilation
of these characteristics along with other criminal history factors come together to
shape an offender’s relative risk of various negative outcomes (e.g. re-arrest,
revocation, re-incarceration).
In the 1980s, the National Institute of Corrections (NIC) utilized the Model
Case Management Systems Project to move the country in the direction of a
workload model (see Clear, 2005).2 The NIC model was never fully embraced
and is rarely considered today. The American Probation and Parole Association
(APPA) addressed the workload/caseload issue, in the 1990s, in which total
caseload was a function of case priority (high, medium, or low) and hours each
month devoted to each of these types of cases (ranging from 4 hours to 2 hours or
1 hour, respectively). Separating workload and caseload as distinct aspects of
study and concern reflect what is referred to as the risk, needs, and responsivity
model (RNR). Community corrections supervision practices are influenced by the
research by Andrews and Bonta (2010), among others (e.g. Taxman et al., 2004)
that have found that more intense levels of supervision should be reserved for those
presenting a higher likelihood of having a negative supervision outcome (e.g. re-
arrest, revocation). Similarly, those with lower likelihoods of failure should be
sentenced to fewer conditions of supervision. The RNR approach recognizes that
there are not only static (i.e. unchanging) features that predict risk, but that
supervision practices should focus on the dynamic elements of an individual’s life
to reduce likelihood of a negative outcome. This could be in the form of substance
abuse treatment, employment training, education, and other deficits that increase
the probability of a negative outcome. These needs are targeted at the individual
by being responsive to each person’s learning capacity and readiness for change.
Taking these elements of RNR together, NIC, APPA, and others suggest community
corrections officers should spend more time with higher-risk individuals (see
Burrell, 2006, and Table 1).
A workload model recognizes that offender and jurisdictional differences can
result in more or less officer time spent per offender. The APPA model above
42
Probation Journal 65(1)
Table 1. Supervision caseload approach (APPA, 1991).
Case Priority
Hours per Month
Total Caseload
High
4 hours
30 cases
Medium
2 hours
60 cases
Low
1 hour
120 cases*
*This is based on 120 work hours per officer each month. Table adapted from DeMichele, 2007: 13.
suggested that ‘high’ level offenders need twice the amount of time to supervise
(according to agency requirements) than a ‘medium’ level offender, and four times
the time required to supervise a ‘low’ level offender. Although this model suggests
that probation agencies should move away from an approach that only counts
cases, it is a simple formula for determining officer caseload standards. Simply, how
do we know that high-risk offenders take twice as long as medium-risk offenders?
What tasks do officers complete with high-risk offenders that necessitate twice as
much time? This is not to suggest that higher-risk offenders do not or should not take
longer to supervise, but there is a lack of empiricism documenting the tasks officers
complete with offenders.
Measuring officer workload is a necessity for determining officer staffing levels,
and such an approach can be used to inform policy. Workload studies have been
used in probation for at least the past 40 years. In fact, Miles (1969) pointed...
To continue reading
Request your trial