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Buying Justice: Judicial Elections

Buying Justice: Judicial Elections . Source: Brennan Center for Justice. Source: Brennan Center for Justice. Theory of Change. 1. What change do we want?. Who has the resources to create that change?. 2. 3. What do they want?. What do we have that they want?. 4. Previous Research .

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Buying Justice: Judicial Elections

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  1. Buying Justice: Judicial Elections

  2. Source: Brennan Center for Justice

  3. Source: Brennan Center for Justice

  4. Theory of Change 1 What change do we want? Who has the resources to create that change? 2 3 What do they want? What do we have that they want? 4

  5. Previous Research • Joanna Shepherd, Justice at Risk an Empirical Analysis of Campaign Contributions and Judicial Decisions. 2013. • Joanna Shepherd, Money, Politics, and Impartial Justice. 2008. • Michael S. Kang & Joanna Shepherd, The Partisan Price of Justice: An Empirical Analysis of Campaign Contributions and Judicial Decisions. • Michael S. Kang & Joanna Shepherd, The Partisan Foundations of Judicial Campaign Finance • Alicia Bannon & Lianna Reagan, New Politics of Judicial Elections 2011-2012. • James Sample, Adam Skaggs, Jonathan Blitzer, & Linda Casey The New Politics of Judicial Elections, 2000-2009: Decade of Change. 2010.

  6. Model #1 Model #2 The States Illinois (partisan elections) Pennsylvania (partisan elections) Wisconsin (nonpartisan elections) Michigan (nonpartisan elections) New York (partisan trial court elections) New Jersey (does not have elections) Connecticut (The Missouri Plan) The States New York New Jersey Control Variables • Judge Level • Case Level • State Level

  7. The Model The fully controlled, estimated standard OLS regression models are the following: Model 1 Judicial_decisionit= B0Constantit + B1PAJIDit + B2Contribution_percenit + B3PAJIDit+ B4Partisanit+ B5Demit + B6Repit + B7Otherit + B8Tort_climateit + B9Size_firmitεit Model 2 Judicial_decisionit= B0Constantit+ B1Public_finan + B2PAJIDit + B3Contribution_percenit + B4PAJIDit+ B5Partisanit+ B6Demit + B7Repit + B8Otherit + B9Tort_climateit + B10Size_firmitεit

  8. Next Steps: • Crowdsourcing the data • Continuing to edit the model

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