Comment va la vie au Canada ?
Bibliographic record
Abstract
De manière générale, le Canada obtient des résultats supérieurs à la moyenne de l’OCDE sur la plupart des indicateurs du bien-être ci-après. Il se situe aux premiers rangs des pays de l’OCDE pour ce qui est du patrimoine net des ménages, le taux d’emploi est élevé (73 % en 2016), le taux de chômage de longue durée est faible (0.8 % en 2016) et moins de 4 % des salariés travaillent régulièrement 50 heures ou plus par semaine, soit moins d’un tiers de la moyenne de l’OCDE. Cela étant, selon les informations recueillies, les travailleurs à temps plein ont en moyenne moins de temps de loisir (temps consacré aux loisirs et aux occupations personnelles) que dans la plupart des autres pays de l’OCDE.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.014 | 0.010 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".