The Right Space: The Impact of Meaningful Dialogue in Informing Culturally Safe Care in the Emergency Department in a Rural Northern Community
Bibliographic record
Abstract
This project focused on emergency department (ED) care provided in a rural northern Canadian community. It studied how supported and meaningful dialogue between health authority providers and physicians whose work is associated with the ED, and providers who work with Indigenous people outside the health authority, helped inform culturally safe care in the ED. Guided by Indigenous and non-Indigenous advisory committee members, this participatory action study created a space for dialogue that allowed the perspectives of two worlds and multiple disciplines to emerge and develop solutions. The findings demonstrated what culturally safe and unsafe care in the ED look like, identified current culturally safe practices, and described factors that challenge culturally safe care. This project, although small, was unique because of the degree of collaboration in health care improvement between those inside and outside the health authority. Supportive dialogue that is mutually negotiated to include attention to culturally safe practice may be the starting place for the creation of the right space, the ethical space, which is so crucial in moving forward. From this foundation, there are six priority suggestions on how to enhance culturally safe care within an ED setting. These recommendations, built from dialogue within a locally generated ethical space, may extend beyond the local context and may be crucial for supporting cultural safety more broadly in the health care system. The findings presented here were the result of a research project undertaken as part of a master’s degree and do not reflect the views of any other body.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.030 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.047 | 0.037 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.004 | 0.021 |
| Research integrity | 0.003 | 0.005 |
| 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".