The NC-CAFO dataset includes hand-validated images of poultry and swine CAFOs and control images throughout the state of North Carolina from the US Department of Agriculture (USDA) National Agricultural Imagery Program (NAIP).
fcc-comments is an annotated version of the comment corpus from the Federal Communications Commission’s (FCC) 2017 “Restoring Internet Freedom” proceeding. The comment data were processed to be in a consistent format (machine-readable pdf or plain text), and annotated with three types of information: whether the comment was cited in the agency’s final order, the type of commenter (individual, interest group, business group), and whether the comment was associated with an in-person meeting.
Python implementation of BM25 relevance ranking algorithm with weighting option designed to work with corpuses that have a large amount of duplication.
The code and data in this repository will replicate the comment scoring and analysis conducted in “Do fake online comments pose a threat to regulatory policymaking? Evidence from Internet regulation in the United States.”
The code and data in this repository will replicate the tables and figures in the main body of “Deep Learning to Map Concentrated Animal Feeding Operations.” Includes manually tagged and modeled CAFO point locations.
Interactive graphics depicting trends in racial and ethnic achievement gaps for all 50 states, and how the gaps relate to socioeconomic inequalities between groups.
Interactive maps of the patterns and trends in residential income segregation over the past forty years in the two dozen most populated metropolitan areas of the United States.