Cultural Safety Training for Health Professionals Working with Indigenous Populations in Montreal, Québec
Bibliographic record
Abstract
Urban Indigenous populations face some of the most significant barriers to access to health services out of any population in Canada. The Indigenous community in Montreal developed a cultural safety training program to help decrease some of these barriers. An extensive review of published literature on cultural safety in health care was performed. A training program was developed to: describe the diversity of Indigenous populations in Montreal; explain historic and present-day determinants of health inequities in this population; develop competencies to respect clients’ diversity and promote cultural safety in care. A pre-test survey was circulated to participants to establish baseline knowledge and attitudes towards Indigenous populations. The program was divided into 3 half-day sessions. After each session, a satisfaction evaluation grid survey was circulated to participants. The Indigenous Cultural Safety Training Program was presented to a total of 45 nurses, social workers, and physicians with frequent interactions with the Indigenous community in Montréal. Having an Elder and community member present appeared to have been successful in increasing participants level of awareness of the importance of improving the quality of health care services provided. Challenges were identified regarding the transmission of the political aspect of the cultural safety concept, and the importance of decolonizing health care systems. Reflections on how to address these in the future will be discussed. Cultural safety training for health professionals is challenging, yet, a necessity to improve access to care and improve health outcomes in urban Indigenous populations.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".