Bibliographic record
Abstract
A partir des donnees de l'Enquete sur les capacites de lecture et d'ecriture utilisees quotidiennement (ECLEUQ) de Statistique Canada, nous avons etudie les differences de revenus entre les minorites et les Blancs et l'importance des capacites cognitives dans les modeles de revenus observes. Certains groupes de minorites ont des capacites de lecture et de calcul considerablement inferieures (d'apres les tests) a celles des Blancs et d'autres groupes de minorites ayant mieux reussi sur le plan economique. Par ailleurs, chez certains groupes d'hommes, ces differences expliquent en grande partie les modeles de revenus observes. Les ecarts salariaux entre les groupes ethniques et les Blancs sont, toutefois, beaucoup moins importants chez les femmes; et les variables des capacites de lecture et de calcul n'expliquent pas vraiment ces ecarts. Il est question, dans ce document, des diverses incidences sur les politiques generales.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 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".