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ABSTRACT
The 2015 Baltimore Riots, which occurred following clashes between residents and police during anti-police brutality protests, were the most widespread acts of civil unrest to grip the city since 1968. The civil unrest raised questions about whether policymakers had misdiagnosed the intensity of resident dissatisfaction with neighborhood conditions or the ease at which the death of a black resident in police custody would ignite outrage. I use data from the 2014 Baltimore Citizen Survey, a city-commissioned satisfaction survey, to examine resident perceptions of police a year before the unrest and to examine which individual and contextual factors shaped dissatisfaction with quality of life in the city. Results from one-way ANOVA, factor analysis, and multivariate regressions show that race and economic distress were significant predictors of dissatisfaction. Furthermore, blacks, Millennials, and residents of certain planning districts were highly dissatisfied with police and with the availability of resources. High levels of dissatisfaction were reported by areas which would become flashpoints of the 2015 unrest. I discuss the implications of racial, spatial, and social cleavages in satisfaction for city governance, including how citizen surveys, as policy feedback devises, can attune policymakers to the attitudinal, demographic, and experiential profiles typically correlated with civil unrest.
Correction Statement
This article has been republished with minor changes. These changes do not impact the academic content of the article.
Acknowledgements
I thank representatives from Baltimore City’s Bureau of the Budget and Management Research for providing the anonymized survey data and associated reports. I thank Mike Galdi and Christian O’Neill in the Baltimore City Department of Planning for providing shapefiles and other data. I thank Rhoanne Esteban, University of California Santa Barbara, for assistance with geocoding locations related to the unrest. I thank Candis Watts-Smith, Christopher Stout, Loren Henderson, Derek Musgrove, Kimberly Moffitt, the anonymous reviewers, and the editors for helpful comments and suggestions. Any remaining errors are my own. Earlier versions of this manuscript were presented at the 2017 annual meetings of the National Conference of Black Political Scientists and of the Midwest Political Science Association.
Disclosure statement
No potential conflict of interest was reported by the author.
Notes
1 I do not use the word “riot” in deference to the nomenclature preferred by most city residents who are unaffiliated with the police or city government. City reports refer to what happened as the “Baltimore City’s April 2015 Civil Unrest.” The Fraternal Order of Police refer to what happened as “the 2015 Baltimore Riots.”
2 See also Jackson (Citation2016).
3 Schaefer Center for Public Policy, University of Baltimore, Baltimore City Citizens Survey Final Report (October 2009), 3.
4 PCA not supported: KMO was 0.617 and only 50% of variance explained by one factor.
5 The Distressed Communities Index, “including the licensed dataset, constitute confidential and propriety information of EIG” and “cannot be disseminated or disclosed to a third party.” EIG provided the author the dataset under limited nontransferable use as defined by a university-approved data use agreement.
6 Per the EIG documentation, “[t]he DCI is based on data from the American Community Survey (5-year estimates 2010–2014) and the 2010 and 2013 Zip Code and County Business Pattern data.” Distress scores are calculated based on a geography’s rank on each of the seven equally weighted variables. The ranks are then averaged and normalized to be equivalent to percentiles, resulting in the distress score – the higher the score, the greater the economic distress.
7 BCS data identified only the respondents’ planning district, not respondent’s police district. Planning districts and police districts were organized for different purposes (Mike Galdi, GIS Analyst, Baltimore City Department of Planning, personal communication with author, September 20 2017). See Appendix Table 2 for descriptive statistics on districts. See Appendix Figure 2 for side-by-side comparison. Crime reports at the zip code level were also less reliable.
8 See Appendix Table 8 for descriptive statistics.
9 Perception of Safety Index means were 0.62 for all, 0.62 for whites, 0.63 for blacks, and 0.59 for other minorities.
10 Zip code level Herfindahl–Hirschman Index (HHI) scores computed using four racial categories: non-Hispanic whites, non-Hispanic blacks, Hispanics, and non-Hispanic other racial minorities (M = 0.55, SD = 0.15, range 0.37–0.93). A 1.0 HHI indicates a locale where everyone has the same race; a 0.0 HHI indicates a racially/ethnically diverse locale. ANOVA results for race and HHI index were significant: F(2, 643) = 19.92, p < .001, η2 = 0.06. Zip code distress and zip code HHI were strongly positively correlated (r = 0.229; p < .000).
11 The MLM intercept standard deviation of 1.7 for Lifestyle Resources suggested that respondents could have regional specific intercepts up to 3.4 higher or lower than average about 95% of the time. Likewise, the deviation of 2.35 for Physical Resources meant that respondents could have regional specific intercepts up to 4.7 higher or lower than average.
12 Interclass correlations were 0.04 (Lifestyle Resources) and 0.06 (Physical Resources). These low ICC estimates suggested that (1) the IVs were not significantly different across the planning districts, (2) any variance in the DVs was due to respondent differences within the districts rather than between them, and (3) multilevel modeling was unnecessary.
13 US Department of Justice, Civil Rights Division, Investigation of the Baltimore City Police Department, August 10 2016.