Bibliographic record
Abstract
La thématique de ce numéro de la revue est atypique. Plutôt que d’aborder d’importantes questions telles les relations entre sciences sociales et littérature, la migration des jeunes, l’héritage intellectuel de Fernand Dumont et ainsi de suite, le numéro présente des recherches utilisant des ensembles de données disponibles auCentre interuniversitaire québécois de statistiques sociales(CIQSS). Historiquement, les organismes gouvernementaux de statistiques sont imputables, entre autres, d’administrer des recensements, de tenir des enquêtes sur la population active pour estimer le taux de chômage, de calculer les flux commerciaux à partir des documents administratifs du service des douanes, etc. Les organismes de statistiques de certains pays se sont limités, plutôt délibérément, à ce type d’activités, définies par leur obligation de fournir aux gouvernements la base d’informations nécessaires aux fins de l’administration. C’est, dit-on parfois, le choix qu’a fait le Bureau australien de la statistique.
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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.253 | 0.113 |
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".