Provincial Autonomy and the 2023 Federal-Provincial Healthcare Deal: A Federalism Deficit at Work?
Bibliographic record
Abstract
The fallout of the COVID-19 pandemic put enormous strain on healthcare services across the country, leading Canadian premiers to call on the federal government to negotiate a new healthcare deal. The dynamics of these negotiations received extensive media coverage and highlighted some of the most fundamental issues in Canadian federalism. The objective of this article is to explore whether the 2023 healthcare negotiations were conducted in accordance with core federalism principles (e.g. autonomy, constitutionalism, partnership), or if they rather reflect some form of federalism deficit. More specifically, it asks whether, and to what extent, provincial autonomy was challenged through conditional federal funding to health care. The authors conclude that the formal division of constitutional powers is blurred through the federal government’s use of its “spending power,” and that the state of intergovernmental relations in Canada has undermined the principle of equal partnership between Ottawa and the provinces within the federal system.
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 | 0.012 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.014 | 0.010 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".