A Multidimensional Approach to Explore the Experiences with Ethnic Matching amongst Chinese Social Service Practitioners in the Greater Toronto Area
Bibliographic record
Abstract
Abstract In multicultural societies, social workers often work with people of diverse cultural backgrounds. As one of the strategies to facilitate social workers’ cultural competence in diverse settings, they are often matched with clients of the same or similar cultural backgrounds. This practice is called ethnic matching and is commonly utilised in ethno-specific and immigrant-serving organisations. This practice has been extensively studied in the literature and is believed to be beneficial to treatment acceptability and service quality. Nonetheless, most of the existing literature focuses on the practitioner–client dyad without taking the broader context into consideration. This study adopted a multidimensional cultural competence approach to examine Chinese practitioners’ lived experiences of serving Chinese immigrants in the Greater Toronto Area (GTA). Six focus groups were conducted (n = 34), and data were analysed using a grounded theory approach. Results show themes across four levels: (i) personal: personal experience as a motivator; (ii) interpersonal: shared culture and language as a double-edged sword; (iii) organisational: service target shifts and increased difficulty to ethnically match and (iv) community: intracommunity heterogeneity and mismatch. This study provides recommendations for social workers, educators and policymakers to consider when applying ethnic matching in cross-cultural settings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.008 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".