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Brian Weinstein

@brian-weinstein.bsky.social

Froyo enthusiast, Quant UX Researcher @Google

2 Posts222 Follower395 Folgt
Dr Michele V@micheleveldsman.bsky.social · last mo.

“I have done all of the things that one is supposed to do to earn a tenure-track position. And I have done approximately 85% of them by typing prompts into a large language model and then moderately editing the output.” 🤣🤣🤣 brilliant 👌🏽 open.substack.com/pub/inprepar...

Opinion: I Was Not Allowed To Type Prompts Into ChatGPT During My Chalk Talk And This Is Discrimination

By Dr. Rachel Simmons, Postdoctoral Fellow, Stanford University

open.substack.com

Anine Hartmann@aninehartmann.bsky.social · last yr.

This paper, looking at how important lighting levels are for road safety by calculating the amount of moonlight at the time of every car-pedestrian crash going back decades, is ingenious. 🌕🌖🌗🌘🌑 Really interesting work. The thread below is a great and thought-provoking read 🤩

Justin Tyndall@justintyndall.bsky.social · last yr.

My paper, Road Illumination and Nighttime Pedestrian Deaths: Evidence from Moonlight, is now published at Economics of Transportation. authors.elsevier.com/a/1kptw_oIvi...

Brian Weinstein@brian-weinstein.bsky.social · 2y ago

This is wild. "By age 85 more than half of the population becomes errors, by age 100 ‘young liar’ errors constitute the entire population"

Health Nerd@gidmk.bsky.social · 2y ago

This may be my favourite preprint (or even paper) of the year. Dr. Saul Newman's latest work looks at the global data on very old people, and shows that it's probably garbage. The paper basically shows that the global information on people aged 85+ is likely all errors. Remarkable. 1/n

Screenshot of the preprint and abstract. Title: The global pattern of centenarians highlights deep problems in demography Abstract: Accurate age data is fundamental to medicine, social sciences, epidemiology, and good government. However, recent and heavily disputed debates on data quality have raised questions on the accuracy of demographic data at older ages. Here, we catalogue late-life survival patterns of every country in the world from 1970-2021 using comprehensive estimates of old-age populations provided by global governments and curated by the United Nations. Analysis of 236 nations or states across 51 years reveals that late-life survival data is dominated by anomalies at all scales and in all time periods. Life expectancy at age 100 and late-life survival from ages 80 to 100+, which we term centenarian attainment rate, is highest in a seemingly random assortment of states. The top 10 ‘blue zone’ regions with the best survival to ages 100+ routinely includes Thailand, Kenya and Malawi – respectively now 212th and 202nd in the world for life expectancy, the non-self-governing territory of Western Sahara, and Puerto Rico where birth certificates are so unreliable they were recently declared invalid as a legal document. These anomalous rankings are conserved across long time periods and multiple non-overlapping cohorts, and do not seem to be sampling effects. Instead these patterns suggest a persistent inability, even for nation-states or global organisations, to detect or measure error rates in human age data, with troubling implications for epidemiology, demography, and medicine.