Une comparaison du PIB par habitant au Canada et aux Etats-Unis de 1994 a 2005
Bibliographic record
Abstract
Le propos de cette étude est d'examiner les différences du produit intérieur brut (PIB) par habitant entre le Canada et les États-Unis de 1994 à 2005. L'étude démontre que l'écart du PIB par habitant entre les deux pays a légèrement rétréci au cours de cette période. Elle décompose également cet écart en deux sous-composantes - la productivité et l'intensité du travail - et montre que leur importance relative a considérablement changé après 2000. Si l'écart de production a diminué légèrement depuis 2000, c'est principalement en raison d'un accroissement des heures travaillées par habitant au Canada par rapport aux États-Unis.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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; both teacher heads agree on what is shown here.
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".