Intergovernmental Relations in Canada's Immigration System: From Bilateralism towards Multilateral Collaboration
Bibliographic record
Abstract
Abstract This article has two objectives. The first is to highlight a turn towards multilateral collaboration in the immigration sector and the resulting focus on pan-Canadian policy objectives and initiatives. This account is set against the current literature, which argues a bilateral approach to intergovernmental relations in the sector has resulted in asymmetrical policies and programs. The second objective is to demonstrate the value of explicitly focusing on the nature of intergovernmental relations as unilateral, bilateral or multilateral. Applying this lens, the article draws out the drivers and complexity of the turn towards multilateral collaboration in the immigration sector, arguing it is motivated by an increased provincial engagement in economic immigration and also by the federal government's desire to reassert its own role in response.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.023 | 0.015 |
| Scholarly communication | 0.013 | 0.002 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".