Socialized Healthcare and Women’s Fertility Decisions
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
Resul Cesur⇑, Pinar Mine Gunes⇑, Erdal Tekin⇑ and Aydogan Ulker⇑ Resul Cesur is an associate professor of healthcare economics in the Department of Finance at University of Connecticut, a research fellow at the Institute of Labor Economics (IZA), and a research associate at the National Bureau of Economic Research (NBER). Pinar Mine Gunes is an assistant professor in the department of economics at University of Alberta. Erdal Tekin is a professor of public policy in the School of Public Affairs at American University, a research fellow at the IZA, and a research associate at the NBER. Aydogan Ulker is an associate professor of economics in the department of economics in Deakin Business School. cesur{at}uconn.edu gunes{at}ualberta.ca tekin{at}american.edu ulker{at}deakin.edu.au
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 | 0.000 | 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