Bibliographic record
Abstract
Il est estimé qu’environ 8 millions des Canadiens, soit 23% de la population canadienne, s’identifient comme francophones (1). De ces 8 millions, près d’un million vivent en situation minoritaire, dispersés dans des régions majoritairement anglophones tels que l’Ontario, les maritimes, les provinces de l’ouest et les régions du nord canadien (1). En tant que minorités linguistiques, les Franco-canadiens ne sont pas étrangers aux inégalités qui assaillent le tissu social au Canada. Bien qu’il existe peu de recherche récente à ce sujet, il est bien connu que les communautés francophones dans un contexte minoritaire ont tendance à être moins scolarisées, moins nombreuses sur le marché du travail, ont un revenu moyen moins élevé que la population anglophone et se concentrent souvent à des endroits marqués par une économie instable (2). Étant donné le faible statut socioéconomique des Canadiens français en situation minoritaire, il n’est pas surprenant de constater que ces individus rapportent une perception individuelle de leur santé plus basse que les anglophones majoritaires (3).
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.024 | 0.003 |
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".