Employment Supports for Newcomers in Small and Middle-sized Communities andRural Areas: Perspectives of Newcomers and Service Providers
Bibliographic record
Abstract
In recent years there has been an increased migration of highly skilled and educated cohort of men and women from their initial port of entry—large urban centers such as Toronto, Vancouver, and Montreal—to smaller urban/rural communities as a result of regionalization of the Canadian immigration policies. This article examines the employment supports for newcomers in Grand Erie—an urban/rural area in Ontario—which is now a home to an unprecedented number of newcomers. Using a community-based participatory research methodology, data were gathered from 212 newcomers and 237 service providers through quantitative and qualitative responses in the survey questionnaires. Results show that newcomers faced many challenges including non-recognition of foreign credentials, unemployment, language barriers, and discrimination. Collaboration between newcomers, service providers, social workers, and government is vital to foster newcomer integration in this region as well as in other smaller communities.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".