Unemployment and Mortality in France, 1982-2002
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
This study uses aggregate panel data on 96 French départements for the period from 1982 to 2002 to investigate the relationship between macroeconomic conditions and mortality. We estimate linear regression models with local area and time fixed effects. The main finding is that higher local unemployment rates are associated with significant reductions in mortality. The sign and magnitude of the effects are quite consistent with several recent studies using data from other countries. Models of mortality by source indicate that the negative relationship between unemployment and mortality is strongest for deaths due to cardiovascular disease and accidents. We thank Marie Laure Monteil, Eric Jougla and Eric Desquesses for making available the mortality and unemployment data we use in this study. Thanks also to Sabina Ohri who provided able research assistance. Chris Ruhm, Dean Lillard and seminar participants at McMaster University and the ASHE Conference provided helpful comments and suggestions. All remaining errors are ours.
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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 | 0.000 | 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 | 0.000 | 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) | 0.028 | 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