A Socioeconomic Scale for Canada: Measuring Occupational Status from the Census
Bibliographic record
Abstract
Cet article présente une nouvelle échelle professionnelle pour la classification nationale des professions (CNP) au Canada. En premier, l'on discute le contexte historique dans lequel la production des échelles des professions, faites par des sociologues aux Canada et aux États‐Unis, s'est réalisée. La méthodologie de la récente échelle Nam–Powers–Boyd utilisée aux États‐Unis est ensuite appliquée au recensement des professions de 2001. Celle‐ci sert à créer des scores des statuts professionnels pour les titres professionnels de la classification nationale des professions (CNP 2001) à Statistiques Canada. Ces scores soulignent les inégalités démographiques et socio‐économiques qui existent parmi les groupes au Canada. L'article se termine par une discussion des débats courants concernant l'utilisation des scores composites professionnels. This paper provides a new occupational scale for the Canadian National Occupational Classification system. The historical context for occupational scales produced by sociologists in Canada and the United States is first discussed. The methodology used in the recent Nam–Powers–Boyd scale in the United States then is applied to the 2001 census of occupations to construct occupational status scores for the occupational titles found in the National Occupational Classification for Statistics (2001) at Statistics Canada. The occupational status scores highlight inequalities existing among groups in Canada along demographic and socioeconomic dimensions. The paper concludes with a discussion of current debates over the use of composite occupational scores.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".