Income Disparities: The Case of Unskilled Workers in Canada (1996-2010)
Why this work is in the frame
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Bibliographic record
Abstract
In this paper we analyse the gaps in economic welfare that exist between skilled and unskilled labor in Canada. Following the work of Chardon [1] [2] and Amossé and Chardon [3], we use compe- tency levels as defined in the National Classification of Occupations to distinguish these two groups and then analyse the income disparities that exist between them. Our main findings show that unskilled workers are worse off economically than their skilled counterparts and that the Canadian workforce seems to be more bipolarized than the Canadian population as a whole. We also find strong intra-categorical inequalities within unskilled labor, workers from the sales and services occupational domain being at a disadvantage relative to their peers in other occupational groups. Finally, we show that state intervention, through taxation and social transfers, plays an important role in tightening the inter-categorical and intra-categorical income gaps.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it