Research Lab
Parents often select schools by relying on subjective assessments shared by other parents—which are increasingly becoming available on school ratings websites in the form of written reviews. We apply recent advances in natural language processing to analyze nearly half a million reviews posted by parents for over 50,000 publicly-funded US K-12 schools on a popular ratings website.We find: i) schools in urban areas and those serving affluent families are more likely to receive reviews; ii) review language correlates with standardized test scores—which are known to closely track race and family income—but not school effectiveness, measured by how much students improve in their test scores at the school over time; and iii) the linguistics of reviews reveal several racial and income-based disparities in K-12 education. These findings suggest that parents who reference school reviews may be accessing, and making decisions based on, biased perspectives that reinforce achievement gaps.
An AI interface that turns raw conversation audio into interactive maps
Research
An LLM-Powered Framework for Analyzing Collective Idea Evolution and Voting Dynamics in Deliberative Assemblies
Research
Supporting decision makers in effective and efficient constituency-informed, AI-supported decision-making. Communicating how constituen...
Research
A curated social experience that transforms dinner between strangers into an opportunity to reimagine how we listen, speak, and share
Research
Over 40 young people participated in a social listening experiment exploring how personal experiences build bridges to better understanding current events and creating mo
Pilots & Programs
A new civic infrastructure in Boston grounded in dialogue as a way to building “civic muscle” of democracy
Pilots & Programs