Our semi-regular rundown of the Federal Reserve’s Beige Book is full of story ideas for reporters across beats. The April edition spotlights key economic trends by region, including a New Jersey salon struggling to find qualified hires, and declining tourism from Canada and Mexico across the U.S.
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We break down the types of employees who work for the U.S. government along with laws and regulations that define how federal workers have, until recently, typically been hired and fired.
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Reporters reveal how they accessed a huge tranche of Medicare data and offer tips on notetaking for data analysis, using AI for coding and exercising persistence when seeking sources.
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San Francisco Chronicle investigative reporters Jennifer Gollan and Susie Neilson share tips for building a national database from scratch, interviewing trauma survivors, negotiating with public records officials and more.
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Managing expectations, gaining buy-in from newsroom leaders and more: What two research teams found after months embedded in global newsrooms experimenting with artificial intelligence tools.
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As the second administration of President Donald Trump seeks to limit authorized and unauthorized immigration, get to know key facts and data sources about immigrant workers.
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The Journalist’s Resource and Econofact recently hosted a webinar featuring two trade economists and an NPR producer whose reporting teams have covered tariffs. Watch the recording and read key takeaways.
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We spotlight free data sources journalists can use to report on economic issues ranging from GDP and inflation to economic inequality, along with topics outside of economics, such as education spending.
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Our periodic rundown of the Federal Reserve’s Beige Book is full of story ideas for reporters across beats. We reveal story pitches from the most recent release, including holiday decorator woes in the Midwest and grocery store staffing travails in Montana.
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In a field experiment involving more than 400 fictitious LinkedIn profiles, researchers find connection requests sent from Black men’s profiles were 13% less likely to be accepted than those from white men’s profiles.
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