The Art of Sharing: The Richer Provinces Versus the Poorer Provinces Since Confederation
Bibliographic record
Abstract
This thesis examines the social and political history of equalization, which is the federal program that allows all provinces to provide reasonably comparable levels of services for reasonably comparable levels of taxation. It examines why Ottawa adopted this mechanism in 1957, the models that it used for those grants, and how it established the formula based upon per capita tax revenues. The thesis moves from the establishment of subsidies at Confederation across the later decades of the nineteenth century into the twentieth century as politicians and bureaucrats gradually realized that few modern federations survive without relative equality among the member governments. It explores the fierce domestic debates and the Royal Commission studies during this struggle to address fiscal inequalities among provincial governments. It also investigates the international models that Ottawa consulted in its quest to devise equalization, concentrating upon the pivotal influence of Australia on Canada as well as Canadas influence Australia. \n The approach is state-centred because most policy-oriented groups did not consider the issue of fiscal inequality among provincial governments when they pushed for the expansion of social services. As well, the thesis considers the crucial influence of Prime Minister Louis St. Laurent during the federal discussions to devise an equalization formula. Caught in a devastating face-off with Quebec over the collection of tax revenues, St. Laurent defused the confrontation with these unobtrusive, non-conditional grants that equalized key tax revenues. With the adoption of equalization in 1957, Ottawa ensured that all provinces could (almost) afford social programs. That cleared the way for vital federal grants to the provinces for social assistance, post-secondary education, hospital care and eventually Medicare. \n In effect, equalization is the largely overlooked mechanism that has kept the federation together. And the history of its introduction has been too little explored.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.015 | 0.031 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".