Comparaison de l'endettement public dans les provinces canadiennes et dans les États américains : une analyse de sensibilité
Bibliographic record
Abstract
Cet article présente une comparaison de l'endettement de l'ensemble des administrations publiques (incluant une part de la dette fédérale) dans les provinces canadiennes et dans les États des États-Unis pendant la période 2000–2007. L'étude a permis de classer ces 60 entités fédérées, selon 5 concepts de dette publique, de la plus endettée à la moins endettée. Parmi les provinces canadiennes, le Québec (rang moyen le plus bas) et l'Alberta (rang moyen le plus élevé) présentent le bilan le plus stable d'un classement à l'autre; toutes les autres provinces montrent des fluctuations importantes selon les classements. La répartition de la dette fédérale entre les provinces (au Canada) et les États (aux États-Unis), ainsi que les concepts de dette utilisés influencent donc significativement, et dans certains cas de façon très importante, le classement.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".