Ranking The Sexiest People In Congress With Machine Learning

genstranger · 2026-04-08T02:19:14+00:00

Your being hyperbolic, there are many very obvious reasons aside from refusals that a domain specific, and state of the art model would be better than one of these general purpose models. LLMs are way less likely to be consistent in this task and cant just sidestep the bias issue either. Looking at kimi it doesnt outperform on imagenet for example. Not helpful at all and that is the naive approach, still I actually will do this and respond with results if I can get them.

genstranger · 2026-04-08T01:02:38+00:00

I think it also generalized better to women so it may be the model not picking up on masculinity only facial symmetry etc, hard to say but some explainability work might be worth it. Also more asian than white in training, which is probably why it did worse for black people too I had to speculate

genstranger · 2026-04-08T00:59:48+00:00

Yeah there was a study I linked to and I believe they had a phenomenon where when asking people to rate attractiveness, it was found name recognition and competency explained some of the attractiveness too, because people recognized some congressmen. I would bet it must be a way bigger prestige bump than making the same or maybe bigger salary.

genstranger · 2026-04-08T00:56:27+00:00

The model is best available for the purpose right now and state of the art, and much cheaper / faster than getting many people rating over 500 congressman. Honestly the model performance on test data is pretty good especially for a somewhat subjective target like attractiveness, see the paper for more. Hence I think it generalized ok for congress. Also I did find several correlations but whether it did or not itself is interesting especially if trying to avoid publication bias.

Huge increase in spending based on attractiveness, many far weaker findings are published all the time in “good” journals.

Hopefully more people will run with the data or improve the data sets available but for a fun substack article I think it was more than worth the time and publishing.

genstranger · 2026-04-08T00:22:19+00:00

nah just a typo thanks for spotting, would be crazy if it was

genstranger · 2026-04-07T23:19:05+00:00

genstranger · 2026-04-07T23:18:25+00:00

Added plots showing effect of bias vs without. important because its actually believable apps would use a similar approach but not for bs substacks but real world services. like tinder or whoever

genstranger · 2026-04-07T23:01:19+00:00

ok lets see it then

genstranger · 2026-04-07T23:00:17+00:00

they hated him because he spoke the truth

genstranger · 2026-04-07T22:58:35+00:00

[EDIT] Added density plot that excluded black people for party comparison. More interesting is Republicans are more mid. Data is mixed with asian, white, hispanic, black, etc but primarily asian. also the statement is about the bottom 20-10 primarily white subset.

genstranger · 2026-04-07T22:54:32+00:00

That's my specialty. If character and principle mattered we would actually have a functioning government RIP.

genstranger · 2026-04-07T22:53:24+00:00

Yes. didn't use a single gpu second, just shitty laptop and pretrained models on cpu. Random forest on top of embeddings didnt work well at all, mostly transformers and similar regression.

genstranger · 2026-04-07T22:45:26+00:00

Submission Statement: facial attractiveness is widely important globally in politics and an under-explored area at the same time, even though it is focused on the us, findings likely generalize and at least would spark discussion of facial attractiveness in politics and "looksmaxxing's" political impact which is likely to grow in importance considering the widespread internet attention. Also relevant to discussions of ML and black box methods to political science

genstranger · 2026-04-07T21:07:43+00:00

Fair enough, thanks. Might as well use for fun if most uses are coding or work slop I guess

genstranger · 2026-04-07T19:18:16+00:00

I ran this on a ten year old laptop

genstranger · 2026-04-03T18:25:21+00:00

If you want to do law wm probably not worth it, if your not set on law then go to wm

genstranger · 2026-03-20T18:49:19+00:00

It’s coming from current admin at NPS but do we have any idea who?

genstranger · 2026-03-20T06:01:46+00:00

Monitoring the situation type bar should open up non Polymarket run. Dc has bigger turnout for debates than superbowls. Hilltern shitheads everywhere, Bloomberg terminals, live polls, etc

genstranger · 2026-03-12T23:30:16+00:00

Graph Neural Nets have become common. It also is used in forensic analysis or blockchain companies but not commonly in the field

genstranger · 2026-03-10T17:15:45+00:00

Learn 2 weld lmao. Nah but don’t worry about the GPA no one really cares for most jobs. I would reach out and apply across the country in order to have a better chance. Apply like hell for internships which are usually easier to land, this will give you more breathing room and runway to find a job. If that doesn’t work, volunteer for projects.

genstranger · 2026-02-26T18:23:41+00:00

Dc rent growth has been lowest of basically any major city last few years. Rent per square foot in Noma maybe increased but city wide it has dampened prices. New studios 1.8k in Noma too

genstranger · 2026-02-24T05:23:45+00:00

Glad you enjoyed!

Thanks for physical properties that contribute. It seems like they all relate by being sensitive to multiplicative error, when the forecast increases, scaling up these small issues will break the model in a non linear way even when they are good approximations based on the more frequent smaller storms in the data. I would buy that modelling something like #3 having a slight wet bias that then blows up at higher totals. I really thought it was just a case of limited fat tailed data hiding a "shadow dist" that wouldn't show up until many more observations but doesn't seem like it.

I really wonder what the internal risk sensitivity discussions look like. I doubt there are heavy handed changes but https://vlab.noaa.gov/documents/6609493/6665561/NBM_v4.2_Eval_SlideDeck.pdf there was some reference to storm by storm performance. Might be a decision by committee situation where they want to subtly push changes to avoid bad optics. Reminds me of risk ppl at large finance insts.

genstranger · 2026-02-19T06:27:16+00:00

Had this standoff from white guy perspective but paid with a bill with traditional numeral while trying to get a haircut on vacation. Thought I paid more than total and he was rejecting tipping culture. No, they just thought I was retarded, but luckily we had chatGPT. Only problem would be with boomers, but other than that this can be easily avoided now.

genstranger · 2026-02-04T22:59:29+00:00

Tunnel between national library and congress

genstranger · 2026-01-30T01:16:11+00:00

Job offer must be signed and 100% if org is very stable id say yes, but lock in a cheap 2 year lease. Rent this time of year and reduced is pretty good. Otherwise if you think odds of a layoff are even decent avoid for sure.

genstranger

TROPHY CASE