Do Advanced Information Technologies Produce Equitable Government Responses in Coproduction: An Examination of 311 Systems in 15 U.S. Cities

• Author: Benjamin Y. Clark,Sung-Gheel Jang,Bradford Davy,Jeffrey L. Brudney
• DOI: 10.1177/0275074019894564
• Published date: 01 April 2020
• Date: 01 April 2020
• Subject Matter: Articles

https://doi.org/10.1177/0275074019894564

American Review of Public Administration

2020, Vol. 50(3) 315 –327

© The Author(s) 2019

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DOI: 10.1177/0275074019894564

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Article

Introduction

Some of the earliest research on coproduction and citizen

contacts pointed out that it “may be quite important in main-

taining governmental responsiveness” (Jones et al., 1977,

p. 148). The thought at that time was that coproduction could

fill some of the service gaps that governments have, speed-

ing up and improving how they could respond to citizen

demands or needs. Verba and Nie (1972) felt that measuring

how responsive a government was to coproduction was

important because it “can represent a mechanism for social

allocation” (p. 113) and differing actors have different levels

of influence or power within the system that may sway

responsiveness in socially undesirable ways.

Prior to widespread internet connectivity, electronic data-

bases, and the general advances of information technology,

governments were limited in how they could measure and

assess their responsiveness—primarily relying upon survey

data. Recent research on coproduction has allowed for the

study of coproduction in ways that simply were not feasible

in past years because of the data created by advanced infor-

mation technology. As the bureaucracy behind coproduction

becomes more driven by algorithm or mechanical process,

we should expect that the prior biases that gave advantage to

communities with power and privilege should fade—if the

process and design behind the algorithms are themselves

designed with equality in mind.

Recent studies of technologically enabled coproduction

have largely shown that the demand for services across vary-

ing neighborhood-level socioeconomic conditions has at

894564ARPXXX10.1177/0275074019894564The American Review of Public AdministrationClark et al.

research-article2019

1University of Oregon, Eugene, USA

2University of North Carolina Wilmington, USA

3Stony Brook University, NY, USA

4Cleveland State University, OH, USA

Corresponding Author:

Benjamin Y. Clark, School of Planning, Public Policy and Management,

University of Oregon, 1209 University of Oregon, Eugene, OR 97403,

USA.

Email: bclark2@uoregon.edu

Do Advanced Information Technologies

Produce Equitable Government Responses

in Coproduction: An Examination of 311

Systems in 15 U.S. Cities

Benjamin Y. Clark1, Jeffrey L. Brudney2, Sung-Gheel Jang3,

and Bradford Davy4

Abstract

This article seeks to answer the following primary research question: Do governments respond differently to citizen service

requests depending on where those requests originate in the city? This study is particularly salient in the wake of the Black

Lives Matter protests in response to police violence or the gross neglect of infrastructure in Flint, MI. Although numerous

studies have been able to demonstrate bias in policing, few (if any) have looked at biases that may be present in other types

of general government services. Empirical evidence has supported the claims by some that some cities were responding

slower to service requests made in poor and minority neighborhoods than they were in the richer, whiter neighborhoods,

but these earlier works were from an era before 311. The article seeks to fill this gap in the modern coproduction literature

to evaluate whether advanced information technologies enable equitable responses by governments. The results of our 15-

city study of 311 systems (nonemergency service requests made by city residents) demonstrate no systematic differences

in how the cities respond that would indicate a bias against minorities and poorer residents. Unsurprisingly, the effects are

not consistent across all of our sample cities. Although some cities have statistically significant differences showing slower

responses for these neighborhoods and others show quicker, the practical differences are so small as to be of little concern

during our study period (2007–2016).

Keywords

coproduction, 311, ICT, equity