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Patrick Wu

@patrickwu.bsky.social

253 followers 153 following 9 posts

Assistant Professor of Computer Science at American University | Computational Politics, NLP, ML/AI | patrickywu.com

Patrick Wu @patrickwu.bsky.social · 06/03/2025

The correlation is 0.52. Here are the logistic regression results with the interaction term. Interestingly, the coefficient is slightly negative, but the p-value is 0.28.

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Patrick Wu @patrickwu.bsky.social · 05/03/2025

5/ This LLM-based approach also replicates @adambonica.bsky.social's finding that agencies perceived as more liberal are more likely to face DOGE layoffs.

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Patrick Wu @patrickwu.bsky.social · 05/03/2025

3/ Using a logistic regression, I find that this measure is strongly predictive of DOGE layoffs, even when controlling for ideology, annual budget, and total staff.

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Patrick Wu @patrickwu.bsky.social · 05/03/2025

@adambonica.bsky.social showed ideology predicts which agencies experience DOGE layoffs. But what other factors could be driving this? Using a generative LLM-derived measure, I find agencies perceived as knowledge institutions are more likely to experience layoffs, even controlling for ideology. 🧵

Scatterplot showing various U.S. government agencies plotted with the total staff (on a log scale) on y-axis versus likelihood of being perceived as a knowledge institution on the x-axis. Red dots indicate agencies that have experienced DOGE layoffs, while gray dots indicate agencies without layoffs. Agencies like NIH, NSF, CDC, and NOAA appear on the right side (more likely to be perceived as knowledge institutions), while agencies like ICE, DEA, and Secret Service appear on the left side (less likely to be perceived as knowledge institutions).

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