Cyclical Changes in Short-Run Earnings Mobility in Canada, 1982-1996
Bibliographic record
Abstract
The paper by Charles M. Beach and Ross Finnie represents the first attempt to quantify short-term or cyclical changes in earnings mobility in Canada. Mobility analysis can be seen as a complement to the analysis of income distribution. For a given degree of earnings inequality, more earnings mobility corresponds to securing greater labour market opportunity. Using longitudinal income-tax-based data, the authors divide the employed population into eight age/sex groups: entry workers (20–24), younger workers (25–34), prime-age workers (35–54), and older workers (55–64) for both sexes; and divide the earnings distribution into lower, middle and upper regions or earnings intervals based on median earnings levels for the distribution as a whole, and calculate the proportion of workers in each group for all years over the 1982–96 period. They also develop transition matrices that show the probability of moving from one earnings interval to another over a one-year period. They find that there have been major cyclical changes in earnings polarization and that these changes have been concentrated in recessions, notably in the 1990–92 downturn. They also find that men in particular experienced a marked decrease in their net probability of upward mobility in the earnings distribution during recessions, as the probability of moving up fell sharply as did the probability of moving down. The results of the paper are particularly relevant for an understanding of how earnings mobility may be affected by the current economic slowdown.
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.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".