Federalism and Fiscal Policy: The Politics of Equalization in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Fiscal equalization is a key political issue in many federal countries, including Canada. Yet, relatively few scholars have paid systematic attention to the political dimensions of Canada’s federal equalization program. Taking an historical and institutionalist perspective, this article explores the politics of equalization policy in Canada, with a focus on the mid-2000s, a period when equalization policy suddenly became a major source of intergovernmental conflict. The main objective of the article is to explain why and how such political struggles over equalization developed. The explanation focuses on four factors: (i) the importance of executive discretion over the equalization program; (ii) the “inter-state” nature of Canadian federalism; (iii) the concentration of non-renewable natural resources in certain provinces; and (iv) the perceptions that surround the program.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 it