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Big Local News

The Big Local News project is part of the Stanford Journalism and Democracy Initiative. The aim of the project is to collect, process and share U.S. government information and public records data that is difficult to obtain and analyze. Through partnerships with local and national newsrooms, the Big Local team collects, cleans, normalizes, and aggregates local data for wider comparisons across, cities, counties and states. This project examines a wide range of issues including criminal justice, housing, health and education for accountability journalism.

Missing kids: Exploring the pandemic plunge in public school enrollment through homeschooling, private school and population change data

This project is a collaboration between Stanford University, Big Local News and the Associated Press. We worked together to answer the question: “What happened to the kids who left public school during the pandemic?”To answer this question, we collected data at the state level for all public schools, private schools in 35 states and homeschooling in 33 states. There were eight additional states that had incomplete private or homeschool data, where some years were missing or a significant part of the student population was not included.The enrollment data covers three school years: 2019-20, 2020-21, 2021-22. We also provide census population estimates for the school-age population in each state. The summary file has data aggregated for each state and includes our “missing kids” analysis. The detailed files breakdown data by grade or age, where available. More details about each data set with important notes, caveats and sourcing, can be found in the Readme file.Our analysis found that in the 21 states plus D.C. with available data, homeschool enrollment grew by 30 percent and private-school enrollment by 4 percent. Taken together, the increase in nonpublic enrollment explains about 40 percent of the public-school enrollment loss. Decreases in the school-age population account for another 26 percent. That leaves about a third of the public-school decline as unexplained -- students who may be skipping kindergarten, in unregistered homeschooling, truant, etc.

Stanford School Enrollment Project 2020-2021

The Stanford School Enrollment Project aims to collect, process and standardize local enrollment data, then make it available to journalists for use in vital news coverage. The enrollment project began as a unique partnership with Stanford education experts, the New York Times, EdSource, a California educational news site; Colorado News Collaborative, a news coalition for local newsrooms; OpenNews, a community journalism project; and Big Local News, a project of Stanford University’s Journalism and Democracy Initiative. This project represents a unique collaboration to find out what happened to K-12 enrollment during the pandemic year when schools were largely offering distance learning to their students. The project is part of Big Local News, which collects local data to discover the regional or national patterns that will yield stories with impact and has built a data-sharing platform for journalists.The project's goal was to get more timely and detailed data than what the U.S. Department of Education would provide.The need to track just how many students were no longer enrolled in classes has become acute for communities across the country amid the Covid-19 pandemic. But federal data on school enrollment typically lags far behind the state-level data. The most recent data made available nationwide was at the state level and did not break out grade level information.The data collected as of late July 2021 represents approximately 70,000 schools in 33 states for the 2019-20 and 2020-21 school years and for up to six years. The database includes school- and district-level enrollment figures. This includes grade-level breakdowns. Where possible, we also collected race and ethnicity information and joined the data to other information on poverty, ELL (English-Language Learner) programs and more.In the fall of 2020, Big Local News data journalists and Stanford University students began researching what education data could be collected at scale as part of The Covid Local News Collaboration. This effort is a partnership between OpenNews and Big Local News which was funded by a 2020-2021 Magic Grant from The Brown Institute for Media Innovation, based at both Stanford and Columbia Universities. The aim of the collaboration has been to help journalists tell deeper, data-driven stories that assist communities responding to Covid-19. This work began with needs-finding efforts by OpenNews. Local journalists surveyed were clear on a critical topic: the need to understand what was happening with local schools because of the pandemic. After more discussion, the Big Local News team settled on collecting school- and district-level enrollment data and standardizing the information across jurisdictions. The federal government does collect this data from states but that information is released as much as a year after it is first collected.The Magic Grant funded several students who began to scour state websites and reach out to state officials to get the data they report to the federal government. In some cases, this meant filing public records requests and in others it meant delving into the differences in reporting methods state by state, or even school district by school district.At the same time, we began partnerships with news organizations already working to collect school enrollment information. Stanford education professor Thomas S. Dee and doctoral student Elizabeth Huffaker joined in and provided guidance for the project. They also began work on using the enrollment data and additional data on school policies to author a paper about the impact on schools.This data can be used to evaluate trends across schools in 33 states. Additional state data will be added as it is collected. The standardized enrollment data are available to download (by state location) and in a state file, district file and schools file. We provide these data in CSV format. The data also can be accessed and analyzed at https://biglocalnews.org and at https://stanford-school-enrollment-project.datasette.io/. Datasette is a tool to analyze and publish data developed by Simon Willison, a 2020 JSK Journalism Fellow and co-founder of Django.The original, unprocessed data we collected contain even more information. We do not document the raw data, but we do provide any documentation we have. Please contact us to access the unprocessed records.Additional contributors include: Simon Willison of Datasette; Vignesh Ramachandran and Laura Frank of CoLab.

Journalism

Using public records for academic research

Government Information

Journalism

Stanford Libraries' Journalism collections include both print and online books and journals, as well as databases and datasets for the study of topics such as news reporting, media ethics, investigative journalism, and data journalism.

The data behind "Climate Cash", a Reuters special report

A report from Conservation Services' summer intern