Earnings dynamics in Canada: an econometric analysis
Bibliographic record
Abstract
This paper reports the results of an empirical analysis of earnings dynamics in the Canadian labour market based on earnings data based drawn from tax returns between 1982 and 1994. Individuals ’ movements up and down quintiles of the earnings distribution are analysed using a hazard model approach. This represents one of the first studies for any country which models mobility across the entire distribution of earnings, including the middle and upper ranges as well as the lower ranges. The effects on transitions between quintiles are analyzed for the following variables: elapsed time spent in a given quintile (i.e., duration dependence effects), age, sex, geographical region, area size of residence, family status, language and overall macroeconomic conditions. One principal finding is that the conditional probability of transiting up or down the earnings distribution depends negatively on the elapsed time that an individual has spent in a given quintile. The earnings mobility patterns appear to be cyclical and exhibit some tendency of reversion to the mean, whereby the conditional probability of upward (downward) mobility is higher for those individuals presently situated in the lower (higher) quintiles.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".