Law, the Social Sciences & Public Policy

Systematic review of case law using traditional methods is generally quite labor intense and time consuming, however new technology allows for more ambitious and systematic evaluation of the evolution of legal doctrine. Using digitized published opinions from the Caselaw Access Project and combining both traditional close reading of case law and text as data techniques, this project focuses on demonstrating how the advent of new text as data methods and digital case sources generates an opportunity for more efficient, transparent, replicable and systematic doctrinal research. After initial presentation of the project at the inaugural Caselaw Access Project at Harvard in 2019, I now have several papers under way that assess the evolution of arbitrary and capricious review, ask what harms are irreparable, and examine judges determine whether law is impermissibly vague. I am scheduled to present on this project at conferences in January and March 2021.

How can we develop better tools for grounding our discussions of civil procedure, court reform, and (ultimately) dispute resolution in our society? What sorts of empirical data would help the legal community have focused discussions about what we do and how our legal system works? This collaborative project, an initiative of the UCLA-RAND Center for Law and Policy, is developing a systematic dataset of civil litigation in Los Angeles Superior Courts–the single largest state court system in the country.

This collaborative project, funded by UCLA’s Sustainable LA initiative, examines the determinants of residential solar panel adoption in Los Angeles, as a window into the legal and policy implications of the determinants of environmentally-conscious consumer decision-making. Policy-makers and researchers often focus on traditional utility maximization models of consumer decision-making, however our research shows that heterogeneity in consumer decision-making approaches, and their values and ties to community (above and beyond simple measures of environmental attitudes), can dramatically affect the adoption of residential solar. Our analyses draw empirical data from a detailed survey we designed and conducted of 3000 Los Angeles home owners, and leverages this data to develop agent-based models that demonstrate the relevance of assumptions about consumer choice on the efficacy of policy interventions in promoting solar energy.

James Syme (RAND) and I are in the process of writing a book chapter on gerrymandering in comparative perspective and developing systematic data, analysis and tools to help improve how we incorporate communities of interest in the redistricting process.

Abstract: Should parents have the freedom to block potentially offensive language, sexuality, and violence from the films their children watch at home? Should an adult with reservations about explicit material be allowed to experience Titanic without that film’s one notorious nude scene, or Schindler’s List without its most uncomfortable audio and video moments? And are these freedoms rightly limited by the relevant decisionmaker’s ability to engage the fast-forward and mute buttons quickly enough, or should copyright law make room for more sophisticated solutions, even over the objections of a hostile copyright community? In this Article, we offer a unique contribution to this long-running debate: detailed data about what consumers would mute and excise from Hollywood films if only they could. Specifically, we report on the decisions made by roughly 300,000 viewers as they filtered and then watched nearly 4 million movie streams during calendar year 2016. The data, we argue, make a strong case in favor of a permissive copyright regime where viewers would have significant freedom to filter films according to their own religious, moral, and public policy convictions.

Abstract: Social scientists predominantly engage in ‘mid-level’ theorizing and empirical research, which presents distinct challenges for building models. The default theoretic and empirical approaches vary across social scientific disciplines, and the validity of most social scientific theoretical and empirical research is context-dependent, making integration and cumulation of knowledge difficult. Social scientific modelers need to be aware of the challenges in building models based on mid-level theoretical frameworks and empirical research where the most common causal mechanisms involve unobserved, and potentially unobservable, mental states. This chapter begins with an overview of key social scientific theoretic frameworks that researchers draw on to build models, focusing in turn on atomistic models of individual behavior before turning to social determinants of individual behavior and theories of interaction and group behavior. While the range of theoretic frameworks used across the contemporary social sciences is diverse, they share common features that create distinct challenges for data collection and model building. With these challenges however come opportunities for building useful social scientific models that leverage cross-disciplinary perspectives and a wider range of social scientific theories.

Part of a special issue on Digital Methods in Asian Studies.

Abstract: Traditional techniques used to study political engagement—interviews, ethnographic research, surveys—rely on collection of data at a single or a few points in time and/or from a small sample of political actors. They lead to a tendency in the literature to focus on “snapshots” of political engagement (as in the analysis of a single survey) or draw from a very limited set of sources (as in most small group ethnographic work and interviewing). Studying political engagement through analysis of social media data allows scholars to better understand the political engagement of millions of people by examining individuals’ views on politics in their own voices. While social media analysis has important limitations, it provides the opportunity to see detailed “video” of political engagement over time that provides an important complement to traditional methods. We illustrate this point by drawing on social media data analysis of the protests and election in Thailand from October 2013 through February 2014.