Identifying Sibling Influence on Teenage Substance Use
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
Joseph G. Altonji, Sarah Cattan and Iain Ware Joseph G. Altonji is Thomas Dewitt Cuyler Professor of Economics at Yale University and a Research Associate at NBER. Sarah Cattan is a Senior Research Economist at the Institute for Fiscal Studies. Iain Ware is a Principal at Bain Capital. The authors are grateful to the referees, Jerome Adda, Monica Deza, Greg Duncan, Patrick Kline, Amanda Kowalski, Costas Meghir, Robert T. Michael, and participants in seminars at UC Berkeley, Brigham Young University, University of Chicago, The European Institute, MIT, New York University, the NLSY97 conference at the Bureau of Labor Statistics (May 2008), NBER Health 2009 Summer Institute, the Institute for Fiscal Studies, UC San Diego, the SOLE/EALE 2010 Meetings, Stanford University, the University of Toronto, and Yale University for valuable comments.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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