Bibliographic record
Abstract
AIM: This paper reports a study the aim of which was to further understanding of cultural safety by focusing on the social health of a small immigrant community of Muslims in a relatively homogeneous region of Canada following the terror attacks on 11 September 2001 (9/11). BACKGROUND: The aftermath of 9/11 negatively affected Muslims living in many centers of Western Europe and North America. Little is known about the social health of Muslims in smaller areas with little cultural diversity. Developed by Maori nurses, the cultural safety concept captures the negative health effects of inequities experienced by the indigenous people of New Zealand. Nurses in Canada have used the concept to understand the health of Aboriginal peoples. It has also been used to investigate the nursing care of immigrants in a Canadian metropolitan centre. Findings indicated, however, that the dichotomy between culturally safe and unsafe groups was blurred. METHOD: The methodology was qualitative, based on the constructivist paradigm. A purposive sample of 26 Muslims of Middle Eastern, Indian or Pakistani origin and residing in the province of New Brunswick, Canada were interviewed in 2002-2003. Findings. Participants experienced a sudden transition from cultural safety to cultural risk following 9/11. Their experience of cultural safety included a sense of social integration in the community and invisibility as a minority. Cultural risk stemmed from being in the spotlight of an international media and becoming a visible minority. CONCLUSION: Cultural risk is not necessarily rooted in historical events and may be generated by outside forces rather than by longstanding inequities in relationships between groups within the community. Nurses need to think about the cultural safety of their practices when caring for members of socially disadvantaged cultural minority groups as this may affect the health services delivered to them.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.005 |
| 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".