Re-estimating the Gainful Employment Rate of Older Men: the United States, 1870 to 1930.
Bibliographic record
Abstract
Analyses of the economic effects of the introduction of the public pension system on older men in the US have been hamstrung by difficulties generating reliable estimates of historical labor-force participation rates using data from early US censuses that only asked respondents about their occupations and not whether they were actively employed. We extend a unique feature of the 1901 Canadian census, which asked about retirement status as well as occupation, to older men in the 1900 US Census to estimate labor-force participation rates that adjust for misreporting of employment status. Our estimates show that reported rates substantially overestimate labor-force participation among older men. We also show that adjusted rates based on an econometric correction for misclassified limited dependent variables produces are similar to those based on the 1901 Canadian census. Using this technique to extend our adjustment shows that reported rates overstate older men’s labor-force participation rates in the 1880, 1910, 1920 and 1930 census, as well as the decline in those rates between 1900 and 1910.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".