Predicting court verdicts - algorithmically!

[18ba102]

For the longest time, I’ve been wondering about how we can predict decisions of Courts. Obviously, there are several variables which go into a verdict - known knowns (facts of the case), known unknowns (judicial bias, although Paul Novosad’s research on bias shows that it isn’t really a thing), unknown knowns and unknown unknowns.

But even then, research from other jurisdictions have shown that it is possible in limited cases to predict outcomes. Here’s some exciting research from the US on predicting US Supreme Court verdicts in Right to Counsel cases:

Predicting Supreme Court Decisions Mathematically: A Quantitative Analysis of...

“The study is designed to demonstrate that, in at least one area of judicial review, it is possible to take some decided cases, to identify factual elements that influenced the decisions, to derive numerical values for these elements by using a formula, and then to predict correctly the decisions of the remaining cases in the area specified.”

Putting this out here so others with similar interests can weigh in!

[saurabh_karn]

@18ba102

e been wondering about how we can predict decisions of Courts. Obviously, there are several variables which go into a verdict - known knowns (facts of the case), known unknowns (judicial bias, although Paul Novosad’s research on bias shows that it isn’t really a thing), unknown knowns and unknown unknowns.

But even then, research from other jurisdictions have shown that it is possible in limited cases to predict outcomes. Here’s some exciting research fr

Wondering how complex it is to replicate and baseline for Indian legal context. I do know that Paul’s dataset can be used to do a lot of cool stuff but the underlying data itself may not be that clean and might require some effort.

[18ba102]

Research from the US: Determining ideological leanings of US Supreme Court judges (1989)

Ideological Values and the Votes of U.S. Supreme Court Justices | American...

"Acquiring independent measures of the ideology of Supreme Court justices is not a simple task. As part of a separate study we conducted a content analysis on the ideological values of all justices from Earl Warren to Anthony Kennedy from newspaper editorials in several of the nation’s leading newspapers. We started by conducting a content analysis of a source that contains comparable information on each justice since Earl Warren: statements in newspaper editorials from the nomination by the president until the confirmation vote by the Senate.

To conduct the content analysis, we trained three students to code each paragraph for political ideology. Paragraphs were coded as liberal, moderate, conservative, or not applicable. Liberal statements include (but are not limited to) those ascribing support for the rights of defendants in criminal cases, women and racial minorities in equality cases, and the individual against the government in privacy and First Amendment cases. Conservative statements are those with an opposite direction. Moderate statements include those that explicitly ascribe moderation to the nominees or those that ascribe both liberal and conservative values.

The justice’s ideology (JI) is then measured by
the formula JI = (liberal - conservative) / (liberal + moderate + conservative).

This formula leads to a scale ranging from +1.0 (unanimously liberal) through .0 (moderate) to -1.0 (unanimously conservative)."