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Brendan Schuetze

@schu.etze.co

Cognition, Learning Science, Quant Methods Assistant Professor, Educational Psychology at a “large university in the mountain west” Views may not be my own, but definitely not my employer's schu.etze.co

117 Posts924 Follower471 Folgt
Brendan Schuetze@schu.etze.co · 3mo ago

This should be national news. The mere fact that a single data center anticipated to use 2x the total amount of electricity currently consumed by entire state of Utah can be built based on the yea/nay vote of three county commissioners is absolutely wild

The Salt Lake Tribune@sltrib.com · 3mo ago

Here's a look at the crowd of more than 600 Utahns on hand for the Box Elder County Commission's vote on a massive campus of data centers. (Rick Egan | The Salt Lake Tribune) Read our live updates: https://www.sltrib.com/news/2026/05/04/utah-data-center-backed-by-shark/ 

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Ryan Briggs@ryancbriggs.net · 6mo ago

I have a new paper. We look at ~all stats articles in political science post-2010 & show that 94% have abstracts that claim to reject a null. Only 2% present only null results. This is hard to explain unless the research process has a filter that only lets rejections through.

It must be very hard to publish null results Publication practices in the social sciences act as a filter that favors statistically significant results over null findings. While the problem of selection on significance (SoS) is well-known in theory, it has been difficult to measure its scope empirically, and it has been challenging to determine how selection varies across contexts. In this article, we use large language models to extract granular and validated data on about 100,000 articles published in over 150 political science journals from 2010 to 2024. We show that fewer than 2% of articles that rely on statistical methods report null-only findings in their abstracts, while over 90% of papers highlight significant results. To put these findings in perspective, we develop and calibrate a simple model of publication bias. Across a range of plausible assumptions, we find that statistically significant results are estimated to be one to two orders of magnitude more likely to enter the published record than null results. Leveraging metadata extracted from individual articles, we show that the pattern of strong SoS holds across subfields, journals, methods, and time periods. However, a few factors such as pre-registration and randomized experiments correlate with greater acceptance of null results. We conclude by discussing implications for the field and the potential of our new dataset for investigating other questions about political science.
Eiko Fried@eikofried.bsky.social · 7mo ago

After 5 years of data collection, our WARN-D machine learning competition to forecast depression onset is now LIVE! We hope many of you will participate—we have incredibly rich data. If you share a single thing of my lab this year, please make it this competition. eiko-fried.com/warn-d-machi...

WARN-D machine learning competition is live » Eiko Fried

If you share one single thing of our team in 2026—on social media or per email with your colleagues—please let it be this machine learning competition. It was half a decade of work to get here, especi...

eiko-fried.com

Roland Hatzenpichler@environmicrobio.bsky.social · 9mo ago

“The prohibited activities would include joint research, co-authorship on papers, and advising a foreign graduate student or postdoctoral fellow. The language is retroactive, meaning any interactions during the previous 5 years could make a scientist ineligible for future federal funding.”

U.S. Congress considers sweeping ban on Chinese collaborations

Researchers speak out against proposal that would bar funding for U.S. scientists working with Chinese partners or training Chinese students

science.org