Evolving federalism : intergovernmental relations and multilevel governance in Canada
Bibliographic record
Abstract
The following research paper investigates the changing character of federalism in Canada, as expressed through intergovernmental relations. Specifically, the impact that individual prime ministers and their governments may have on these relationships is explored. In particular, Stephen Harper and Justin Trudeau’s management styles are compared in order to determine what lasting or significant effect, if any, these individuals have had on how Canada’s federal and provincial governments interact with each other. Secondary literature describing and summarizing Harper’s style of open federalism, in conjunction with primary research on Justin Trudeau’s reversion to a more collaborative style, concludes that though each prime minister was able to have some tangible effects on federal-provincial relations during their time in office, these effects were, or will be, easily overridden by their successors. The following research asks whether Harper and Trudeau’s actual styles of intergovernmental relations were consistent with their rhetoric on the same subject. Though Harper spoke often about his preferred style of open federalism, it appears to many scholars that not all of his actions reflected the core tenets of this model. Likewise, though Trudeau advertised a collaborative, more multi-level approach to governance during the 2015 election campaign and during his time in office, I conclude that much of his efforts to follow up on these principles are symbolic at best. In both cases, it appears that the federal government consistently pursues its own goals, regardless of the rhetoric used to describe provincial involvement, rights, and in Trudeau’s case, genuine collaboration with both the provinces and additional third-party groups.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.017 | 0.009 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".