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
Brain drain effects of migration has been studied extensively. Ability drain has not. While data constraints impede assessments of the extent of ability drain, it is suggestive that immigrants or their children founded over 40% of the Fortune 500 US companies. This paper examines migration’s impact on productive human capital or ‘skill’ as a function of ability and education for source country residents and migrants under a points system that accounts for education (as in Canada pre-2015) and a ‘vetting’ system that also accounts for ability (as in the US H1-B visa program). It concludes that migration results in an ability drain that is larger than the brain drain; is more likely to result in a net skill drain than a net brain drain; that a vetting system is more likely to augment net skill drain; and that inequality in migrants' source countries raises both brain and ability drains.
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 | 0.035 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.001 | 0.008 |
| Insufficient payload (model declined to judge) | 0.000 | 0.014 |
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