Exploring Culturally Appropriate Ways of Supporting Newcomers to Canada: A Collaborative Family Intervention Model for Child Protection
Bibliographic record
Abstract
| Background: The newcomer communities in the Edmonton region identified the gaps in their experience with Children’s Services including the need for cultural and linguistic interpretation and support systems when dealing with child welfare authorities. The Collaborative Family Intervention Model between the Multicultural Health Brokers Coop (MCHB) and the Edmonton Region’s Children’s Services examined in this presentation seeks to respond to the call from the communities to fill those gaps. This presentation is part of a larger research project exploring the ‘intermediary’ role that Cultural Brokers play in negotiating the relationship between newcomer families and child welfare workers. Methods: We analyzed 61 Collaborative Family Intervention Model documents using a Grounded Theory approach, which shed light on how the Collaborative Model emerged, its transformation over the last decade, and its current capacity to respond to newcomers dealing with child protection. Results: Preliminary results elucidate: the social factors that bring newcomer families into contact with child welfare authorities (poverty, violence against women); the key elements of the practice of MCHB Cultural Brokers and Children’s Services workers, which help prevent entry or re-entry of children into provincial care (building trust); the past and current policies of MCHB and Children’s Services (joint protocols); and, future plans to expand the Collaborative Model. Conclusions: Analysis to date indicates that the Collaborative Model is generally meeting the needs of newcomer communities, but external and internal factors ought to be addressed to better support these communities and better prevent the entry or re-entry of children and youth into provincial care.
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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 | 0.013 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.018 | 0.015 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".