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Crowdsourcing Reliable Local Data

Published online by Cambridge University Press:  20 September 2019

Jane Lawrence Sumner Open the ORCID record for Jane Lawrence Sumner [Opens in a new window] ,
Emily M. Farris Open the ORCID record for Emily M. Farris [Opens in a new window]  and
Mirya R. Holman Open the ORCID record for Mirya R. Holman [Opens in a new window]
Jane Lawrence Sumner
Affiliation:
University of Minnesota, Political Science, 1414 Social Sciences, 267 19th Ave S, Minneapolis, MN 55455, USA. Email: [email protected]
Emily M. Farris
Affiliation:
Texas Christian University, Political Science, Scharbauer Hall 2012G, Fort Worth, TX 76129, USA. Email: [email protected]
Mirya R. Holman*
Affiliation:
Tulane University, Political Science, 6823 St. Charles Avenue, Norman Mayer Building, New Orleans, LA 70118, USA. Email: [email protected]
*
*Email: [email protected]
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Abstract

The adage “All politics is local” in the United States is largely true. Of the United States’ 90,106 governments, 99.9% are local governments. Despite variations in institutional features, descriptive representation, and policy-making power, political scientists have been slow to take advantage of these variations. One obstacle is that comprehensive data on local politics is often extremely difficult to obtain; as a result, data is unavailable or costly, hard to replicate, and rarely updated. We provide an alternative: crowdsourcing this data. We demonstrate and validate crowdsourcing data on local politics using two different data collection projects. We evaluate different measures of consensus across coders and validate the crowd’s work against elite and professional datasets. In doing so, we show that crowdsourced data is both highly accurate and easy to use. In doing so, we demonstrate that nonexperts can be used to collect, validate, or update local data.

Keywords

data collectioncrowdsourcingsurveysreplicationlocal politics
Type
Articles
Information
Political Analysis , Volume 28 , Issue 2 , April 2020 , pp. 244 - 262
Copyright
Copyright © The Author(s) 2019. Published by Cambridge University Press on behalf of the Society for Political Methodology.

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Footnotes

Authors’ note: Sumner is an assistant professor of political science at the University of Minnesota, Twin Cities. Farris is an associate professor of political science at Texas Christian University. Holman is an associate professor of political science at Tulane University. All authors contributed equally to this work. This paper was previously presented as “Is 2chainz the Mayor of Atlanta? The Crowd Says ‘No”’ at the 2018 Saint Louis Area Methods Meeting (SLAMM) and the 2018 Political Methodology meeting in Provo, Utah. Thanks to Vito D’Orazio, Justin Grimmer, Justin Esarey, participants at 2018 SLAMM and 2018 PolMeth meetings, and four anonymous reviewers for helpful comments on the paper. The University of Minnesota and Tulane University provided monetary support for this research. All errors remain our own. All data from the project are available from Holman, Sumner, and Farris (2019) “Replication Data for: Crowdsourcing reliable local data”, doi:10.7910/DVN/LSEEKB, Harvard Dataverse.

Contributing Editor: Jeff Gill

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Sumner Dataset

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