Hostname: page-component-76fb5796d-9pm4c Total loading time: 0 Render date: 2024-04-27T18:08:17.450Z Has data issue: false hasContentIssue false
  • English
  • Français

The Essential Role of Statistical Inference in Evaluating Electoral Systems: A Response to DeFord et al.

Published online by Cambridge University Press:  02 December 2021

Jonathan N. Katz Open the ORCID record for Jonathan N. Katz [Opens in a new window] ,
Gary King Open the ORCID record for Gary King [Opens in a new window]  and
Elizabeth Rosenblatt Open the ORCID record for Elizabeth Rosenblatt [Opens in a new window]
Jonathan N. Katz
Affiliation:
Kay Sugahara Professor of Social Sciences and Statistics, California Institute of Technology, DHSS 228-77, 1200 East California Boulevard, Pasadena, CA 91125, USA. Email: jkatz@caltech.edu, URL: jkatz.caltech.edu
Gary King*
Affiliation:
Albert J. Weatherhead III University Professor, Institute for Quantitative Social Science, Harvard University, 1737 Cambridge Street, Cambridge, MA 02138, USA. Email: King@Harvard.edu, URL: GaryKing.org
Elizabeth Rosenblatt
Affiliation:
Post-BA Affiliate, Institute for Quantitative Social Science, Harvard University, Cambridge, MA, USA. Email: ERosenblatt@alumni.harvard.edu, URL: elizabethrosenblatt.com
*
Corresponding author Gary King
Get access Rights & Permissions [Opens in a new window]

Abstract

Katz, King, and Rosenblatt (2020, American Political Science Review 114, 164–178) introduces a theoretical framework for understanding redistricting and electoral systems, built on basic statistical and social science principles of inference. DeFord et al. (2021, Political Analysis, this issue) instead focuses solely on descriptive measures, which lead to the problems identified in our article. In this article, we illustrate the essential role of these basic principles and then offer statistical, mathematical, and substantive corrections required to apply DeFord et al.’s calculations to social science questions of interest, while also showing how to easily resolve all claimed paradoxes and problems. We are grateful to the authors for their interest in our work and for this opportunity to clarify these principles and our theoretical framework.

Keywords

redistrictingrepresentationfairnessstatistical inference
Type
Article
Information
Political Analysis , Volume 31 , Issue 3 , July 2023 , pp. 325 - 331
Copyright
© The Author(s) 2021. Published by Cambridge University Press on behalf of the Society for Political Methodology

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Edited by Lonna Atkeson

References

DeFord, D., et al. 2021. “Implementing Partisan Symmetry: Problems and Paradoxes.” Political Analysis, forthcoming.CrossRefGoogle Scholar
Gelman, A., and King, G.. 1994. “A Unified Method of Evaluating Electoral Systems and Redistricting Plans.” American Journal of Political Science 38 (2): 514–554. https://j.mp/unifiedEc.10.2307/2111417CrossRefGoogle Scholar
Grofman, B., and Brunell, T. L.. 2005. “The Art of the Dummymander: The Impact of Recent Redistrictings on the Partisan Makeup of Southern House Seats.” In Redistricting in the New Millennium, edited by Schwartz, I. M., 183–199. Lanham, MD: Lexington Books.Google Scholar
Katz, J. N., King, G., and Rosenblatt, E.. 2020. “Theoretical Foundations and Empirical Evaluations of Partisan Fairness in District-Based Democracies.” American Political Science Review 114 (1): 164–178. https://GaryKing.org/symmetry.10.1017/S000305541900056XCrossRefGoogle Scholar
King, G. 1989. “Representation through Legislative Redistricting: A Stochastic Model.” American Journal of Political Science 33 (4): 787–824. https://j.mp/2o46Gkk.CrossRefGoogle Scholar
King, G., Keohane, R. O., and Verba, S.. 1995. “The Importance of Research Design in Political Science.” American Political Science Review 89 (2): 454–481. http://gking.harvard.edu/files/abs/kkvresp-abs.shtml.CrossRefGoogle Scholar
Olson, D., and Fusco, S.. 2012. “Rules versus Standards: Competing Notions of Inconsistency Robustness in Patent Law.” Alabama Law Review 64 (3): 647–696.Google Scholar
Rosenblatt, E. M. 2017. “Judging Gerrymandering: Improving Methods for Measuring Partisan Distortion and Its Component Parts.” Bachelor’s Thesis, Harvard College (Presented at the Tufts Redistricting Conference May 2017). https://nrs.harvard.edu/urn-3:HUL.InstRepos:38986910.Google Scholar
Wasserman, L. 2012. “Minimaxity, Statistical Thinking and Differential Privacy.” Journal of Privacy and Confidentiality 4 (1). https://doi.org/10.29012/jpc.v4i1.611.CrossRefGoogle Scholar