Very cool calculator!

see: https://xkqr.org/qq/

A nice real-world example of chi-squared for independence.

A sick hack for approximating Pythagorean square roots.

If $c^2 = a^2 + b^2$, then $c = \sqrt{a^2 + b^2} \approx \max(0.9a + 0.5b, a)$.

In this essay, I argue that most claimed psychiatric diagnoses are false. By most, I mean more than half. By claimed psychiatric diagnoses, I mean all the instances where a person is told by a licensed healthcare professional that they have a mental disorder. By false, I mean that the person does not actually have a mental disorder, has a diagnosis different than the one they are given, or has multiple labels when only one is accurate. This is not a debate about the definition of mental illness, and it accepts DSM/ICD diagnoses on their own terms.

Excellent piece.

via: https://www.psychiatrymargins.com/p/making-sense-of-a-world-where-most

how scales work — the chaos survey

Fascinating project.

Stop and think about what this means: the two models that predict constant merge rates over the latter half of the plot are more accurate than the linear growth trend. This corroborates what we eyeballed in the plots: the merge rate has not increased in the latter half of this plot. This means llms have not improved in their programming abilities for over a year. Isn’t that wild? Why is nobody talking about this?

Technology advances forced the Census Bureau to use sweeping measures to ensure privacy for respondents. The ensuing debate goes to the heart of what a census is.

This is a great article on a big-name application of differential privacy: it even features an interview with Dworkin! This, to me, seems like a pretty necessary change to preserve the privacy of folks.

via: https://mit.edu/6.1800/www/tutorials/01-intro.shtml

Much of good survey design is getting a decent model of the mind and incentives of your audience. Egos are predictable. You have to tease it out like taffy, and if the ego is sticking to your results too hard you have to find other questions to trap them.

We want assurances that sensitive information will not be disclosed when aggregate data derived from a database is published. Differential privacy offers a strong statistical guarantee that the effect of the presence of any individual in a database will be negligible, even when an adversary has auxiliary knowledge. Much of the prior work in this area consists of proving algorithms to be differentially private one at a time; we propose to streamline this process with a functional language whose type system automatically guarantees differential privacy, allowing the programmer to write complex privacy-safe query programs in a flexible and compositional way.

Very interesting work here!

via: https://ncatlab.org/nlab/show/short+map#use_for_denotational_semantics

One of the questions of the 2026 acx prediction contest is whether Nvidia’s stock price will close below $100 on any day in 2026. At the time of writing, it trades at $184 and a bit, so going down to $100 would be a near halving of the stock value of the highest valued company in the world.

It’s an interesting question, and it’s worth spending some time on it.

via: https://nebula.tv/videos/notdavid-are-men-actually-lying-about-heights-on-dating-apps/

When someone says something like “The us paid $1.1 trillion for its 2003 invasion of Iraq,” you can think to yourself, “Okay, that’s like a paying for the repairs of a global 100-year natural disaster in the PC age.”

50 Cent Adjusted for Inflation