The Role of the Interprovincial Transfers in the ß-Convergence Process. Further Empirical Evidence for Canada
Bibliographic record
Abstract
Based on the approach of Timljonavich and Vogelsang (2002), I present empirical evidence of the role of the federal transfers on the B-convergence process in Canadian provinces. Using information on personal income for the period 1926-1999, the principal conclusion is that the interprovincial transfers were not determinant or decisive to the attainment of deterministic convergence in the Canadian provinces. Their role have been to accelerate the convergence process, particularly in poorer provinces. / Fondée sur l’approche de Timljonavich and Vogelsang (2002), je présente l’évidence empirique du rôle des transferts fédéraux dans le processus entraînant la convergence B pour les provinces canadiennes. Utilisant l’information sur le revenu personnel pour la période de 1926 à 1999, la principale conclusion qui en ressort est que les transferts inter-provinciaux ne se sont pas avérés déterminants ou décisifs dans l’atteinte d’une convergence déterministique pour les provinces canadiennes. Leur rôle a plutôt été d’accélérer le processus de convergence, en particulier pour les provinces moins nanties.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".