Immigrant integration in small and medium-sized towns and rural areas: local policies and policymaking relations in Canada - Country Reports on multilevel dynamics
Bibliographic record
Abstract
This report looks at multilevel governance dynamics and at the integration policies targeting migrants developed by six small and medium-sized towns and rural areas in Canada between 2016 and 2021. Primarily based on interviews conducted in each of the selected municipalities, it provides an overview of 1) national, regional, and local integration policies targeting migrants in Canada; 2) policymaking relations among the key actors involved in these policy processes in the six localities and key features of policy networks within which these actors interact; 3) how these actors perceive and define integration. The report finds that the political orientation of the federal and provincial governments in Canada greatly influenced the dynamics of multilevel governance of immigrant integration in the selected Canadian localities, whereas municipalities, which could voluntarily elect to play a role in integration, were not obligated to do so as part of their formal political mandate. In Ontario and B.C., selected municipalities had conducted multiple initiatives intended to assist newcomers. These initiatives were unintegrated into municipal integration strategies and were done in an ad hoc manner in response to specific appeals from the local communities. In Quebec, selected municipalities towns had existing integration policies and infrastructure, including municipally or regionally-sponsored integration dialogues that were intended to coordinate social service delivery for newcomers. Immigration was characterized by all interviewees as the primary solution to labour shortages and population decline in the selected localities. Yet, factors like housing availability, affordability, housing size, and transportation were key issues of concern for immigrant integration. Familiarity between actors and active community mobilization facilitated immigrant integration despite the lack of ethnic diversity and the limited resources of integration particularly in smaller localities.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.016 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".