Applying European Ideas on Federalism and Doing It Better?: The Government of Canada’s Homelessness Policy Experiment
Bibliographic record
Abstract
Despite not having explicit authority to legislate on matters local in nature, in 2000 the federal government launched the National Homelessness Initiative (NHI). I argue that this federal program, in many critical aspects, mirrors a governance model developed in the European Union called the Open Method of Coordination (OMC), a model developed in an institutional context whereby the European Commission has no formal authority to coerce member states into coordinating social policy, but nonetheless uses “soft” or voluntary mechanisms to work toward this goal. Vancouver and Toronto are examined more closely to demonstrate how the flexibility of the OMC-style model manifests itself in practice, and the implications for governance, accountability, and effectiveness. I conclude that while the issue of homelessness is principally plagued by insufficient and unstable funding, further application of principles in the OMC model—uniquely applied to the Canadian context—holds promise for improving governance, coordination, and effectiveness of the public policy response to homelessness. Application of the OMC model thus calls for more attention from Canadian federalism scholars and policy-makers.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.028 | 0.015 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.006 |
| 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".