2017
DOI: 10.2139/ssrn.2993009
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Polarization of U.S. Circuit Court Judges: A Machine Learning Approach

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Cited by 2 publications
(2 citation statements)
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“…But recent empirical work has documented that judges do respond to non-legal influences, political and otherwise (Berdejó and Yuchtman, 2013, Ash and MacLeod, 2015, 2017, Chen, Moskowitz and Shue, 2016, Berdejó and Chen, 2017, and Cohen and Yang, 2018. In addition, there is evidence suggesting that the judiciary has become more conservative over time (e.g., Naidu, 2017, Ash, Chen andLu, 2017). This research asks whether we can attribute a causal influence to partisan news media in this trend.…”
Section: Introductionmentioning
confidence: 96%
“…But recent empirical work has documented that judges do respond to non-legal influences, political and otherwise (Berdejó and Yuchtman, 2013, Ash and MacLeod, 2015, 2017, Chen, Moskowitz and Shue, 2016, Berdejó and Chen, 2017, and Cohen and Yang, 2018. In addition, there is evidence suggesting that the judiciary has become more conservative over time (e.g., Naidu, 2017, Ash, Chen andLu, 2017). This research asks whether we can attribute a causal influence to partisan news media in this trend.…”
Section: Introductionmentioning
confidence: 96%
“…As a result, certain words (for instance, the word "think") can be identified to be correlated with a particular behavior (for instance, the level of reasoning in the beauty-contest game, Penczynski, 2016). Coding practices in Economics for quasi-experimental (for instance, Freddi, 2017) and non-experimental (for instance, Gentzkow and Shapiro 2010;Hansen et al 2017;Gentzkow, Kelly, and Taddy, 2017;Gentzkow, Shapiro, and Taddy, 2017;Ash et al 2017) natural language data can provide guidance as to the use of software programs and machine learning techniques. The best practices might be transferred to the analysis of experimental free-form messages.…”
Section: Coding Software Machine Learningmentioning
confidence: 99%