Bibliographic record
Abstract
Dans cet article, j’analyse, à l’aide de diverses méthodes empiriques (régressions sur des données recueillies au moyen d’un panel, variables instrumentales, estimateurs par doubles différences), les règles budgétaires utilisées par les gouvernements provinciaux du Canada de 1981 à 2007. Les résultats indiquent que le type de règles est important, puisque, en moyenne durant la période, les règles d’équilibre budgétaire et les règles relatives à la dette ont été efficaces, alors que les règles relatives aux recettes et aux dépenses ne l’ont pas été. Plus précisément, les estimations par points préférés ont permis d’associer aux règles d’équilibre budgétaire une amélioration des équilibres budgétaires de 0,8 point de pourcentage du PIB ainsi qu’une amélioration des rapports dette-PIB de 1,5 point de pourcentage aux règles relatives à la dette, en moyenne.
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 | 0.005 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".