Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Because minorities typically fare poorly on standardized tests, job testing is thought to pose an equity-efficiency trade-off: testing improves selection but reduces minority hiring. We develop a conceptual framework to assess when this tradeoff is likely to apply and evaluate the evidence for such a trade-off using data from a national retail firm whose 1,363 stores switched from informal to test-based worker screening over the course of on year. We document that testing yielded more productive hires at this firm --raising median tenure by 10-plus percent. Consistent with prior research, minorities performed worse on the test. Yet, testing had no measurable impact on minority hiring, and productivity gains were uniformly large among minorities and non-minorities. These results suggest that job testing raised the precision of screening without introducing additional negative information about minority applicants, most plausibly because both the job test and the informal screen that preceded it were unbiased.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it