Job Attributes and Occupational Changes: A Shift-Share Decomposition by Gender and Age Group for Canada, 2006–2016
Bibliographic record
Abstract
Les changements technologiques ont deux effets de premier ordre sur la nature du travail. Premièrement, les nouvelles technologies peuvent entraîner des changements au sein des professions des personnes sur le marché du travail, et, deuxièmement, elles peuvent pousser ces personnes à passer d’une profession à l’autre. Afin de quantifier ces effets, la présente étude procède à un rapprochement des données détaillées sur les professions tirées des recensements canadiens de 2006 et de 2016 avec des données détaillées qui associent chaque profession à des ensembles de tâches, d’activités et de compétences requises pour cette profession. Les résultats révèlent que l’importance des attributs liés aux interactions sociales et aux tâches cognitives non routinières a augmenté de manière considérable. De plus, la majeure partie de cette augmentation s’est produite au sein de professions étroitement définies. Les hommes ont été plus touchés par les changements observés que les femmes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".