23 Indigenous racism reporting and review process for addressing harm to indigenous patients
Bibliographic record
Abstract
Description To eliminate Indigenous-specific racism and discrimination (ISRD) and make our system safer for Indigenous Peoples, we have developed a process to report and review ISRD events, with a goal to use Indigenous-led restorative approaches for resolution and effect system-level change. This project is aligned with Provincial Health Service Authority’s Integrated Quality and Safety Strategy goal of achieving a culturally safe and anti-racist environment and the foundational documents/obligations from British Columbia’s In Plain Sight Report and Declaration on the Rights of Indigenous Peoples Act. The work included launching Indigenous Self-Identification in patient safety event reporting, forming a Health System wide ISRD response committee (with responsibility to intake events, initiate program-led reviews, approve review reports, and track recommendation implementation), establishing a process for event reviews (protocol), developing resources to support resolution approaches, and creating an evaluation plan. The new ISRD reporting and review process was created to align with the Coast Salish teachings that were gifted to the health authority, and developed through significant engagement and input from leaders, staff and providers across the organization through the formation of an advisory council. Early findings show engagement with Indigenous Health leaders in all ISRD case reviews as well as any patient safety events involving Indigenous patients, increased confidence of leaders in how to review ISRD cases, appreciation from staff for having a way to report ISRD that they witness as a patient safety event, and that many of the reported ISRD events have led to well received resolution and learning through participation in healing circles.
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 | 0.179 | 0.208 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.006 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.038 | 0.022 |
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".