Receipt for run 1: the Lab's permanent record of what it did
Do better-looking professors get better student ratings?
Do better-looking professors get better student ratings?
- Measured in
- rating points per point of looks
- Paper says
- 0.275
- Counts if
- 0.27 to 0.28
- Lab got
- 0.2748
Paper said 0.275. We got 0.2748.
The code and data produced the same result. That doesn't prove the study's method is right.
Check this yourself
You don't have to trust us or the . With Docker and Node installed, this retraces the claim on your own computer and compares the number:
git clone <this repository> && cd rerun && pnpm install && pnpm sandbox:build pnpm verify-claim 5
How much evidence is behind this?
Each step is a tougher test. Only the first one decides who wins the market.
- 1. ✓
The Lab's retrace of the code and data named in the claim
The Lab retraced the code and data and got a number inside the claim's range. YES wins.
- 2. –
Stress test: does the number depend on luck?
Fetching the extra runs…
- 3. –
Rebuilt from the description (experimental)
Fetching the AI's rebuild…
Coming next: a data-leakage check, for the same rows in training and test data, and a maths check on the statistics a paper reports. Neither has run on this claim.
Even all three steps can't prove the science is true. They show how well this result stands up to checking.
Verified
Your browser just re-checked these itself, so you don't have to trust this site.
Checking…
The write-up
The write-up isn't available right now. Its fingerprint is below.
The full record (technical)
✓ Verified on NEAR. See the contract's history
- Outcome
- REPRODUCED
- d0b259198cc3c2ace78fbff438c2e074547728ad977b6141efd77f63b76c31dd
- Commit
- 175eddea88cc8adab8dd20f2100b5b453d359244
- Data fingerprints
- a7d1d8e2a73259faed98ed6abbb3d396b2399c68e59ce6cfc6de94c736c9f1f6
- Software versions fingerprint
- 8dab88328537f15c219ff04f4c55b0150f9867347067f4b5868ed8b0769249af
- Runtime
- 1s, exit code 0
- Started, finished
- 11/12/2026, 10:55:12 PM, 11/12/2026, 10:55:38 PM
- Lab
- lab.rerun-app.near
- Lab code fingerprint
- 2eb776350ac7df5be3d241091996bd81238adc954a7ffbdb9ecea3870e2ae9bf
- AI used
- z-ai/glm-5.3-flash
- 6ae8a8550a54100e678c82dbce10fb9b1b570dc7dd2269213905227c08f6f713
- Signed AI replies
- 016123e58af1456fbc152f491829ef57
- Log fingerprint
- 2355db584fad3eaf8eb305351a9c9c957cc0e6c413455c0f16c0384a63f94296
- Write-up fingerprint
- f1bda7f7f9441891afee294cd26411dbb953c79cdfdd78319705a14ab061f4e7
Show the end of the run log
female -0.239 minority -0.249 non_native -0.253 tenure_track -0.136 lower_division -0.046 one_credit 0.687 looks_effect 0.2748