Using Interval-Level Metrics to Investigate Situational-, Suspect-, and Officer-Level Predictors of Police Performance During Encounters With the Public

AuthorStephen James,Rachel Davis,Elizabeth Dotson,Lois James
Published date01 December 2019
Date01 December 2019
Subject MatterArticles
Using Interval-Level
Metrics to Investigate
Situational-, Suspect-,
and Officer-Level
Predictors of Police
Performance During
Encounters With
the Public
Lois James
, Stephen James
Rachel Davis
, and Elizabeth Dotson
The issue of how to measure the impact of situational-, suspect-, and officer-level
factors on police actions has long been debated in the policing literature. One
promising method is to use interval-level metrics developed via a combined
method of concept mapping and Thurstone scaling. Our objective here was to use
these metrics to score 667 incident reports from a large (n1,500) urban police
department. From this process, we explored significant trends in how police officers
perform during encounters with the public. We found that officers performed better
in “higher stakes” encounters and excelled in vigilance situational assessment as well
as use of tactics and adapting tactics. Officers tended to receive the worst scores in
routine police–citizen interactions and the highest in crisis encounters.
Interpretation and implications of these findings for American policing are discussed.
College of Nursing, Washington State University, Spokane, WA, USA
Elson S. Floyd College of Medicine, Washington State University, Spokane, WA, USA
Corresponding Author:
Lois James, Washington State University – Spokane, 412 E Spokane Falls Blvd, Spokane, WA99210-1495,
Police Quarterly
2019, Vol. 22(4) 452–480
!The Author(s) 2019
Article reuse guidelines:
DOI: 10.1177/1098611119857559
performance metrics, police behavior, incident reports, procedural justice, crisis
A large body of research has examined situational-, suspect-, and officer-level
factors that may influence how police officers behave during encounters with the
public (Engel, Sobol, & Worden, 2000; Fagan, Braga, Brunson, & Pattavina,
2016; Terrill & Reisig, 2003). The majority of this research has focused on the
outcomes of these encounters as the dependent variable of interest. For example,
the questions of whether suspect race influences officer-involved shootings
(James, James, & Vila, 2016; Nix, Campbell, Byers, & Alpert, 2017), whether
officers use greater force against suspects based on their demeanor (Crawford &
Burns, 1998; James, James, & Vila, 2018), and whether neighborhood predicts
the outcomes of police–citizen encounters (Lee, 2016; Sun, Payne, & Wu, 2008)
have dominated the policing literature. Although notable studies have analyzed
process—for example, examining predictors of procedural justice (Holtfreter,
Mastrofski, Jonathan-Zamir, Moyal, & Willis, 2016), measuring police use of
force relative to suspect resistance (Alpert & Dunham, 1997; Hine, Porter,
Westera, Alpert, & Allen, 2018), and de-escalation tactics (Todak & James,
2018)—most have used the outcome of encounters to judge appropriateness
of police behavior.
Focusing on the outcome of police–citizen encounters (e.g., use of force,
arrest rates, or citizen complaints) rather than police performance during the
encounters (e.g., fairness in decision-making, use of de-escalation tactics, or
procedural justice techniques) assigns much of the variation in these encounters
caused by chance, or the actions of others, to the individual officer in question.
Police–citizen encounters are probabilistic in that an officer will never have full
control over the outcome. An officer could behave impeccably and still generate
a citizen complaint, or could treat a citizen fairly yet still have to arrest him or
her. Conversely, an officer could do everything wrong, behave appallingly, and
“get away with it” if the citizen does not feel like making a complaint or believes
making a complaint will have no impact. Thus, measurement techniques that
focus on officer performance have the potential to provide more nuanced infor-
mation about what influences officers’ treatment of the citizens they serve
and protect.
To examine the situational-, suspect-, and officer-level predictors of how
officers perform during encounters with the public, we used interval-level
police performance metrics developed by Vila, James, and James (2018) to
score 667 incident reports from a large urban department. By focusing on
James et al. 453

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