Do Culturally Sensitive Services for Chinese In-Patients Make a Difference?
Bibliographic record
Abstract
Hospitals in large cities provide services to an increasingly diverse linguistic and cultural clientele. Some strategies adopted to improve services to non-English speaking populations include the use of bilingual social workers, interpreters and printed translation tools. In order to identify gaps in culturally sensitive care in a Canadian teaching hospital, this study surveyed a consecutive sample of 279 Chinese in-patients to determine satisfaction with hospital experience, levels of information about hospital routines and awareness of on-site Chinese cultural services. Results were generally positive. However, satisfaction and information levels were significantly higher among those patients who were aware of culturally appropriate Chinese resources such as social workers, cultural interpreters, and culturally specific reference tools. Of particular interest are the 121 patients (44%) who were less comfortable with English, since awareness of culturally specific resources tended to make a greater difference to this sub-group. These results can potentially help health care providers improve services to patients and families from diverse cultural and linguistic groups.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".