Empirical Legal Studies

Advances in Data Selection: Evaluating Police Conduct

While agreement on a common set of metrics facilitates longitudinal studies as well as comparisons across studies, these benefits should not deter fresh new thinking about new sources of data that inform lingering research questions. A new paper by Aurelie Ouss (Penn--criminology) and John Rappaport (Chicago), Is Police Behavior Getting Worse? The Importance of Data Selection in Evaluating the Police, illustrates this point nicely. In it, the authors' analysis of police conduct draws from traditional data sources, including litigation levels and municipal settlement payouts, as well as a relatively new data source: liability insurance claims.

Exploiting 23 years worth of liability insurance data, involving 350 law enforcement agencies and a single insurance carrier, the paper finds that "while lawsuits and [settlement] payouts have trended upwards over the past decade, insurance claims have declined." What the authors conclude is that: "... police behavior is not getting worse; rather, public responses to policing harms are intensifying."

Stata Graphic "Trick" of the Day

For too many (myself included), Stata graphics can be among the more complicated coding tasks. Thus, concrete coding tips for some of the more "exotic" graphics capabilities invariably warrant attention (even if only to satisfy curiosity). In this spirit I pass along a brief discussion concerning coding requirements for a "fan" chart in Stata (here). In an example of what is possible (below), the presentation of a standard "line" chart is graphically enhanced with +/- 1, 2, and 3 standard error "cones."

Conference on Data Science and Law

Prof. Elliott Ash (ETH-Zurich) passed along information on a conference submission deadline extension for the Conference on Data Science and Law, hosted by ETH-Zurich, Switzerland, on 7-8 June 2019. The conference’s submission deadline is now: 12 Feb. 2019. An excerpted conference description and related information follow.

“Interest is growing among scholars from a variety of disciplines and across the globe in research at the intersection of data science and law. In recent years, the digitization of legal texts and developments in statistics and computer science have paved the way for new methodological approaches in this area…. The inaugural Conference on Data Science and Law will convene researchers across disciplines who are interested in this burgeoning field. Scholars in law, social and behavioral sciences, digital humanities, computer science, machine learning, and data analytics are invited to present works-in-progress in all areas of empirical legal studies that involve big data sources or use data science techniques, including natural language processing, machine learning, algorithmic fairness, topic modeling, or network analysis."

For those interested, paper proposals can be submitted directly to: dasa.skopp@gess.ethz.ch, with an email subject line: “Conference Submission”.

Database of State Tort Law Reforms (v.6.1)

Ronen Avraham (Tel Aviv/Texas) recently alerted me to an update of one of the more helpful resources around for those who study torts and tort reform. Specifically, the (DSTLR v.6.1) "updates the DSTLR (5th) and contains the most detailed, complete and comprehensive legal dataset of the most prevalent tort reforms in the United States between 1980 and 2018. The DSTLR has been downloaded more than 2700 times and has become the standard tool in empirical research of tort reform. The dataset records state laws in all fifty states and the District of Columbia over the last several decades...." For direct access to the dataset (in Excel) click here.