Cool paper from 2021 by @mako et al. Leverages #RegressionDiscontinuity to demonstrate that, in this case:

"Algorithmic flags make damage by registered editors (in addition to unregistered editors) much more detectable to moderators and so help moderators focus on damage overall, not just damage by suspicious editors. As a result, the algorithmic flagging system decreases the bias that moderators have against unregistered editors."

https://social.coop/@communitydata/110067853159701195

Regression Discontinuity, or the Stuyvesant High School Effect

Do elite schools, or prison incarcerations, have an effect on students or prisoners? I'd mentioned this a few months back on HN and finally tracked down the source.

The Stuy High effect is addressed in "The Elite Illusion: Achievement Effects at Boston and New York Exam Schools",
Atila Abdulkadiroglu, Joshua D. Angrist & Parag A. Pathak (2014) https://economics.mit.edu/files/9518

Upshot: students who came within two answers of the cuttoff (fallling two points above or below the threshold) of Stuy High admissions ... have very similar life outcomess: indistinguishable AP and SAP scores, and indistinguishable admissions rates to prestigious universities.

Other times effects do matter, in another study by Chen & Shapiro on federal inmate prison assignments, showing harsher incarceration translates to higher recidivisim rates.

In Seth Stephens-Davidowitz, Everybody Lies

NBN interview: https://newbooksnetwork.com/everybody-lies

https://www.worldcat.org/title/everybody-lies-big-data-new-data-and-what-the-internet-can-tell-us-about-who-we-really-are/oclc/1113138700

My HN comment: https://news.ycombinator.com/item?id=29745533

#RegressionDiscontinuity #StuyvesantHigh #Education #BigData #SethStephensDavidowitz #EverybodyLies #Prison #MKiethChen #JesseShapiro