Policy Forum: Equalization and Canada's Fiscal Constitution — The Tie That Binds?
Bibliographic record
Abstract
Canada has had a fiscal equalization system since 1957, and equalization was formally embedded in the constitution in 1982. However, the rationale for equalization, how the concept is defined and applied, and what its effects are or should be are all issues that continue to be vigorously debated in both political and expert circles. This article reviews some of these issues and concludes that, on the whole, equalization has played a useful role in helping Canada to get through the last half-century as well as it has. However, the system could be improved by making it more transparent--for example, by fixing the amount to be distributed at (say) the present share of the federal budget (instead of indexing it to a moving average of nominal growth in the gross domestic product), and making the distributional formula less overtly political by establishing a quasi-independent board to examine the allocation formula from time to time and make recommendations for change. Governments at both the federal and provincial levels would then be more accountable for their actions, as they should be in a democracy.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.023 | 0.011 |
| Scholarly communication | 0.017 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.013 | 0.008 |
| Insufficient payload (model declined to judge) | 0.016 | 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; 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".