If you’re trying to get a handle on evidence from academic research about the state of local news, it’s hard to know where to start. The research is scattered — across disciplines from political science to economics to computer science; across universities; across paywalled journals. To some extent, it’s part of the academic job description to overcome those siloes. But they’re major practical barriers for other audiences — policymakers, funders, working journalists — interested in building an evidenced-based case about the local news crisis and potential solutions, demonstrating the significance of the Local News Research Hub.

To solve this problem, Syracuse University and Rebuild Local News teamed up last fall to build a curated, accessible local news database. Their Local News Research Hub formally launched this month. “Our collective purpose is to provide a central, reliable home for data-driven insights into the changing media landscape,” the team states.

Joshua Darr, director of the Local NExT Lab and associate professor at Syracuse University, credited Democracy Fund’s literature review with laying the groundwork for an expanded, searchable database. The hub comprises about 170 studies total, including the 45 “artifacts” covered in that literature review, along with more than 120 new entries. Among these are peer-reviewed articles, dissertations, books and book chapters, and working papers.

“This is not only bridging academia to news practice or to policymaking,” Darr said; the team made a concerted effort to be multi-disciplinary in building the hub. They plan to continue updating the database, and are accepting submissions of additional research for inclusion.

The hub is searchable by discipline, research topic, and study type. Disciplines include Communication, Computer Science, Economics, Political Science, Public Health, Public Policy, and Sociology; research topics include Business Models, Community Connection, Economic Impact, Polarization, Print, and Voter Turnout and Engagement, among others. Each article in the database includes an AI-generated summary (vetted by at least two human researchers) that’s split into three components: a one-sentence Key Finding, a Study Description, and Practitioner Implications. These brief summaries are intended to help make the database useful and legible to audiences outside academia.

Read the full article about the Local News Research Hub by Sophie Culpepper at Nieman Journalism Lab.