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

• Author: Stephen James,Rachel Davis,Elizabeth Dotson,Lois James
• Published date: 01 December 2019
• Date: 01 December 2019
• DOI: http://doi.org/10.1177/1098611119857559
• Subject Matter: Articles

Article

Using Interval-Level

Metrics to Investigate

Situational-, Suspect-,

and Officer-Level

Predictors of Police

Performance During

Encounters With

the Public

Lois James

1

, Stephen James

2

,

Rachel Davis

1

, and Elizabeth Dotson

2

Abstract

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 (n1,500) 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.

1

College of Nursing, Washington State University, Spokane, WA, USA

2

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,

USA.

Email: lois_james@wsu.edu

Police Quarterly

2019, Vol. 22(4) 452–480

!The Author(s) 2019

Article reuse guidelines:

sagepub.com/journals-permissions

DOI: 10.1177/1098611119857559

journals.sagepub.com/home/pqx

Keywords

performance metrics, police behavior, incident reports, procedural justice, crisis

intervention

Introduction

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