Bibliographic record
Abstract
Abstract We use Census and Labour Force Survey (LFS) data for the period from 1971 to 2012 to investigate whether the Canadian wage and employment structures have polarized, that is, whether wages and employment have grown more in high‐ and low‐ than in middle‐paying occupations. We find that there has been faster growth in employment in both high‐ and low‐paying occupations than those in the middle since 1981. However, up to 2005, the wage pattern reflects a simple increase in inequality with greater growth in high‐paid than middle‐paid occupations and greater growth in middle than low‐paid occupations. Since 2005, there has been some polarization but this is present only in some parts of the country and seems to be related more to the resource boom than technological change. We present results for the US to provide a benchmark. The Canadian patterns fit with those in the US and other countries apart from the 1990s when the US undergoes wage polarization not seen elsewhere. We argue that the Canadian data do not fit with the standard technological change model of polarization developed for the US.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".