Partisan Justice: How Campaign Money Politicizes Judicial Decisionmaking in Election Cases

Source: Joanna M. Shepherd and Michael S. Kang, American Constitution Society, 2016

From the press release:
A new study by independent researchers at Emory Law School finds that the upward spiral of big money fundraising and aggressive politics in state judicial elections pressures judges to become partisan actors who favor their own party in deciding election disputes. Bush v. Gore is by far the most famous of this kind of election case, but state courts decide many similar cases every year, regularly determining who wields power at the state and local level. State judges are under enormous political pressure to join in party-based fundraising and campaign networks to survive what has become a fiercely competitive electoral environment. Analyzing a new dataset of cases from 2005 to 2014, Partisan Justice finds that state court judges are systematically biased by these types of campaign finance and re-election influences to help their party’s candidates win office and favor their party’s interests in election disputes. It provides the first systematic evidence of the hidden influence of raw partisanship and party campaign finance on judicial decision-making in these election disputes.

Especially troubling is that here is little reason to believe that partisanship influences judges only in election cases. If judges are influenced, consciously or not, by party loyalty in election cases, they are likely tempted to do so in other types of cases as well, even if it is methodologically difficult to prove the role partisanship plays. The study, titled Partisan Justice, likely exposes just the tip of the proverbial iceberg.

Partisan Justice Principal Findings:
Judges favor litigants from their own party in head-to-head cases. …..
Campaign finance exacerbates partisan behavior. …..
Judges are less likely to be partisan when they no longer need to run for office. …..
The problem of partisan decision making is arguably getting worse over time. …..
Download the Data