Capacity, voice and opportunity: advancing municipal engagement in Canadian federal relations
Bibliographic record
Abstract
In Canada, municipalities are involved in an increasing number of policy areas, but they remain largely absent from the nation’s system of intergovernmental relations. Municipal representatives do not attend First Ministers’ meetings that gather the Prime Minister and heads of each province and territory. They are also largely excluded from intergovernmental councils or committees focused on specific policy areas. Nor do they participate in the negotiation of most intergovernmental agreements. This paper explores how Canada’s intergovernmental infrastructure could be reformed to include municipalities. It does so through an analysis of how other countries have made space for municipalities in their intergovernmental processes. After drawing five lessons from international experience, the paper concludes with four approaches to reforming intergovernmental relations in Canada: (1) ensure municipalities have the capacity, voice and structures to participate effectively in intergovernmental relations; (2) increase municipal involvement in provincial policy-making, including potentially through co-governed intergovernmental councils; (3) as far as possible, eliminate unfunded mandates(ie responsibilities devolved without adequate funding to discharge them) through, for example, provincial legislation or provincial–municipal intergovernmental agreements that require consultation on the fiscal impacts of draft legislation or regulation on municipalities; (4) strengthen trilateral (national/provincial/municipal) relations, including through location-specific or policy-specific agreements, and trilateral intergovernmental councils.
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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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.051 | 0.024 |
| Scholarly communication | 0.019 | 0.006 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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".