In whose words? Struggles and strategies of service providers working with immigrant clients with limited language abilities in the violence against women sector and child protection services
Bibliographic record
Abstract
Abstract Newcomer and immigrant clients with limited language abilities face communication barriers that can compromise their capacity to make informed decisions about themselves and their children with serious implications for their families. These clients most likely had high proficiency of language in their country of origin but are learning the language of the new host country. Using a phenomenological design to elicit descriptions from and interpret experiences of Canadian‐helping professionals, we conducted four focus groups first with child protection workers, and second with violence against women service providers. Analyses of these data uncovered five themes: (1) enhancing client engagement and self‐agency; (2) advantages and drawbacks in use of interpreters; (3) creative and intensive translation strategies; (4) structural challenges and (5) gender and cultural considerations. Results are organized into an ecological framework in putting forward implications for policy and practice. The over‐arching finding supports that important training and preparation are necessary for service providers to deliver language‐sensitive services. As well, funding levels need to be increased to better match service delivery goals. Newcomer and immigrant clients whose language needs are not adequately met potentially face safety issues and/or fragmentation of their families.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.012 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.003 | 0.011 |
| 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".