Earnings and Employment Probabilities of Men by Education and Birth Cohort, 1982-96: Evidence for the United States, Canada and Australia
Bibliographic record
Abstract
In this paper, we analyse the earnings and employment probabilities of men by \neducation level, birth cohort and age in the United States, Canada and Australia using a \nseries of cross-sectional surveys for each country spanning the years 1982 through 1996. For \nall three countries, more recent birth cohorts of less-skilled men have experienced worse \nlabour market outcomes than men from the same skill group but of earlier birth cohorts, \nceteris paribus. In the United States, the deteriorating labour market outcomes appear as \nlower earnings but not lower employment probabilities. In Canada and Australia, the less \nskilled men from more recent birth cohorts experience lower employment probabilities and \nlower earnings, with the magnitude of the earnings decline by cohort being smaller than was \nthe case for the U.S. This is consistent with the hypothesis that labour market institutions in \nAustralia and Canada have prevented wage levels from declining sufficiently to avoid the \nneed for reductions in employment probabilities. In the United States, wage flexibility may \nhave removed the need for reductions in employment probabilities.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".