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Do Attorney Surveys Measure Judicial Performance or Respondent Ideology? Evidence from Online Evaluations

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  • Thomas J. Miles

Abstract

Which judges are "good" at their jobs, and which are not? The answer may depend on the ideology of whom you ask. Judicial decisions inevitably involve policy making, and lawyers may prefer judges whose policy preferences match their own. This paper tests that prediction with online evaluations of judges. Criminal defense attorneys, a group likely to hold progressive views, make up a disproportionate share of the respondents. The respondents assign lower average scores to Republican appointees, especially female and minority ones, even after controlling for the judges' backgrounds and performance measures. In comments, respondents object to judges with conservative tendencies more often than those with liberal ones. The objections to conservative tendencies correlate with large reductions in a judge's numerical ratings, while objections to liberal ones do not. The results suggest that judicial evaluation surveys should take account of how attorneys' ideology influences their perceptions of judicial performance.

Suggested Citation

  • Thomas J. Miles, 2015. "Do Attorney Surveys Measure Judicial Performance or Respondent Ideology? Evidence from Online Evaluations," The Journal of Legal Studies, University of Chicago Press, vol. 44(S1), pages 231-267.
    • Handle: RePEc:ucp:jlstud:doi:10.1086/682697
    DOI: 10.1086/682697
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    1. Hamermesh, Daniel S. & Parker, Amy, 2005. "Beauty in the classroom: instructors' pulchritude and putative pedagogical productivity," Economics of Education Review, Elsevier, vol. 24(4), pages 369-376, August.
    2. Michael A. McPherson & R. Todd Jewell, 2007. "Leveling the Playing Field: Should Student Evaluation Scores be Adjusted?," Social Science Quarterly, Southwestern Social Science Association, vol. 88(3), pages 868-881, September.
    3. Dobrescu, Loretti I. & Luca, Michael & Motta, Alberto, 2013. "What makes a critic tick? Connected authors and the determinants of book reviews," Journal of Economic Behavior & Organization, Elsevier, vol. 96(C), pages 85-103.
    4. Bonica, Adam & Chilton, Adam S. & Sen, Maya, 2015. "The Political Ideologies of American Lawyers," Working Paper Series 15-049, Harvard University, John F. Kennedy School of Government.
    5. Wang Zhongmin, 2010. "Anonymity, Social Image, and the Competition for Volunteers: A Case Study of the Online Market for Reviews," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 10(1), pages 1-35, May.
    6. Dina Mayzlin & Yaniv Dover & Judith Chevalier, 2014. "Promotional Reviews: An Empirical Investigation of Online Review Manipulation," American Economic Review, American Economic Association, vol. 104(8), pages 2421-2455, August.
    7. Bonica, Adam & Sen, Maya, 2015. "The Politics of Selecting the Bench from the Bar: The Legal Profession and Partisan Incentives to Politicize the Judiciary," Working Paper Series rwp15-001, Harvard University, John F. Kennedy School of Government.
    8. Jeffrey A. Livingston, 2005. "How Valuable Is a Good Reputation? A Sample Selection Model of Internet Auctions," The Review of Economics and Statistics, MIT Press, vol. 87(3), pages 453-465, August.
    9. Thomas J. Miles, 2012. "Racial Disparities in Wiretap Applications before Federal Judges," The Journal of Legal Studies, University of Chicago Press, vol. 41(2), pages 419-458.
    10. Luís Cabral & Ali Hortaçsu, 2010. "The Dynamics Of Seller Reputation: Evidence From Ebay," Journal of Industrial Economics, Wiley Blackwell, vol. 58(1), pages 54-78, March.
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    1. Ash, Elliott & MacLeod, W. Bentley, 2021. "Reducing partisanship in judicial elections can improve judge quality: Evidence from U.S. state supreme courts," Journal of Public Economics, Elsevier, vol. 201(C).

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