Immigrant and refugee social networks: determinants and consequences of social support among women newcomers to Canada.
Bibliographic record
Abstract
Recent immigrants and refugees (newcomers) vary on many dimensions but do share similar challenges. Newcomers must rebuild social networks to obtain needed social support but often face social exclusion because of their race, language, religion, or immigrant status. In addition, most have limited access to personal, social, and community resources. Effects of situational and personal variables on the benefits and limitations associated with the social networks of female newcomers were explored through interviews and focus groups with 87 women from 7 communities. Using thematic analysis, the authors identify 5 sources of informal support across all 7 communities, which were almost exclusively limited to co-ethnic relationships, and the types of support, limitations, and reciprocity within each. Perceived support was strongest from family and close friends and, when support from close relationships was unavailable, from primary care providers. The results suggest that co-ethnic peer support networks may be overwhelmed in newcomer communities because of their limited size and resources.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".