South Asian immigrants' experience of child protection services: are we recognizing strengths and resilience?
Bibliographic record
Abstract
ABSTRACT Ethno‐racial minority families who come in contact with child protection services face unique challenges that include different ideas about appropriate child rearing practices, possibly different definitions of child maltreatment, the possibility of racial biases and service provision that does not address their particular needs. Ethno‐racial minority immigrants encounter additional barriers to services associated with the challenges of settlement in a new cultural environment. Although considerable research has explored these issues, knowledge of the experiences of ethno‐racial families who have been in contact with child protection is limited. The current paper provides insights from a qualitative study that explored the experiences of one ethno‐racial group (South Asians) in Canada. Findings suggest a variety of reasons that families come into contact with the child protection system, and the characteristics of the sample highlight their difficult financial and employment circumstances. Themes include participants' desire to be better informed about the reasons for child protection involvement and about what they can expect from the worker and the agency. They also identified a wish for services that not only recognize their cultural diversity but also respond to the needs of the whole family. In‐home services were especially appreciated. The findings reveal the resilience and personal agency among participants that can be enhanced through strength‐based approaches to practice. Helping others, establishing community networks and developing needed services were avenues of resilience identified.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".