Settling beyond big cities: A scoping review of the Canadian literature on immigration to rural and smaller communities
Bibliographic record
Abstract
Abstract Newcomers are living and working across rural and smaller communities in Canada. However, immigration research and policy are overwhelmingly focused on large, urban centres. Responding to this knowledge gap, this article presents the results from a scoping review of the Canadian literature on immigration outside of Canada's largest cities. An analysis of 90 studies reveals several key trends in the literature related to the geographic focus and themes addressed. The results of the review demonstrate that the majority of studies focus on regions with a high population density that are in close proximity to major urban centres, thus revealing a gap in knowledge regarding settlement across more rural and northern parts of the country. Issues related to settlement services, employment opportunities, welcoming communities, public policy, infrastructure, and retention and secondary migration were the most addressed themes across the literature and represent the diversity of rural Canada. In response to these findings, we conclude with a discussion of the potential opportunities for future research and policy change .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".