OCCUPATIONAL SEGREGATION AND THE GENDER EARNINGS GAP: NEW EVIDENCE FROM SKILLED TRADESWORKERS IN CANADA
Bibliographic record
Abstract
The goal of this paper is to leverage Statistics Canada’s Registered Apprenticeship Information System (RAIS)–T1 Family File (T1FF) linkage to provide the first decomposition results on the gender earnings gap of new skilled tradesworkers. This newly available and extremely rich dataset overcomes many previous data limitations related to this key group of the labour market. The RAIS–T1FF master files are only accessible through the Canadian Research Data Centre Network (CRDCN); no public-use files are available due to the high confidentiality of the data. I applied for and was granted access to these master files through the CRDCN, completed my analysis, and had submitted results for vetting. Due to the sudden and indefinite closure of the CRDCN as a result of the coronavirus pandemic, my vetting request was not completed; therefore, no results are available for release and discussion at this time. Nonetheless, my paper contributes to the literature by presenting emerging stylized facts and novel insight into the RAIS–T1FF linkage.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".