Serving immigrant families: using knowledge translation to inform a family approach in the settlement sector
Bibliographic record
Abstract
Research studies show that the family is an integral dimension of newcomers’ immigration and settlement experiences. Findings from a recent project on the integration trajectories of immigrant families shed light on the ways families support each other and the social factors of immigration. Still, immigration policy, federal data collection and measures, as well as settlement services rely on an individualistic conceptualization of newcomers with insufficient regard for their social realities. Preliminary consultations with partner settlement agencies in the Greater Toronto Area reveal there is a need to incorporate the family/social dimension in their services. Using the Knowledge Translation method, academic knowledge was transferred into a practical position paper for Immigration, Refugees and Citizenship Canada settlement policy-makers. Through ongoing collaboration with the partners, the pillars of a Family Approach for the settlement sector were developed. Five key practical recommendations for its implementation are presented to policy-makers in the paper.
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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 | 0.089 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.015 | 0.017 |
| Scholarly communication | 0.019 | 0.017 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".