Differences de productivite entre les provinces
Bibliographic record
Abstract
La presente etude examine les differences de productivite (PIB par emploi) entre les provinces au moyen d'une analyse de decomposition et d'une analyse de regression. Dans un premier temps, nous etablissons l'ordre de grandeur des differences de productivite entre les provinces, puis nous decomposons ces differences en deux elements, a savoir, les differences de composition industrielle et les differences de productivite au niveau des branches d'activite. Nous examinons aussi le role que jouent les et secteurs de l'economie dans les differences de productivite entre les provinces. Enfin, nous procedons a une analyse de regression afin de determiner la signification statistique des differences de productivite entre les provinces. Nous en arrivons a la conclusion que la Colombie-Britannique, l'Alberta, la Saskatchewan, l'Ontario et le Quebec ne different pas sensiblement pour ce qui est du PIB par emploi si l'on tient compte des differences de composition. Le Manitoba et les provinces de l'Atlantique, pour leur part, accusent un retard sur les autres provinces. L'ecart est attribuable surtout aux differences au niveau des branches plutot qu'aux differences de composition. La forte performance de l'Alberta et de la Saskatchewan doit beaucoup au secteur des ressources naturelles.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".