Anti-Indigenous racism in Canadian healthcare: a scoping review of the literature
Bibliographic record
Abstract
Health inequity between Indigenous (First Nations, Inuit, and Métis) peoples and other citizens is an important policy concern in Canada, as in other colonial countries. Racism in healthcare has been identified as contributing to poorer care and to worse outcomes. Despite a large literature regarding racism in other healthcare contexts, the dimensions of the existing literature on anti-Indigenous racism in Canadian healthcare are unclear. A scoping review examined the evidence of anti-Indigenous racist experiences in healthcare in the research literature, including the types of racist behaviours identified, settings studied, and Indigenous populations and geographic regions included. We identified English and French language journal articles on anti-Indigenous racism in Canadian healthcare settings in Scopus, PubMed, CINAHL, and the Bibliography of Indigenous Peoples in North America, and grey literature reports. A total of 2250 journal articles and 9 grey literature reports published since 2000 were included in screening, and 66 studies were included in the final review. Most used qualitative interviews with patients, but a large proportion included healthcare providers. Most were conducted in urban settings, a majority in Ontario or British Columbia, with mixed Indigenous populations. The largest proportion focussed on patient experiences with healthcare in general, rather than specific clinical contexts. Most racist experiences identified were 'covert' racism, including patients feeling treated differently from non-Indigenous patients, being ignored, treated more slowly, or not believed. Stereotyping of Indigenous peoples as substance users, poor patients, or poor parents was also commonly reported. 'Overt racism', including the use of racist slurs, was not widely found. Some quantitative studies did use standardized or validated instruments to capture racist experiences, but most did not result in generalizable estimates of their prevalence. The few studies linking racism to health outcomes found that experiencing racism was related to reluctance to seek healthcare, potentially leading to higher unmet healthcare needs. Gender was the intersecting dimension most identified as shaping healthcare experiences, with Indigenous women and girls at risk to specific stereotypes. Some papers suggested that socio-economically disadvantaged Indigenous people were at the highest risk to experiencing racism. Types of anti-Indigenous racism identified in Canadian healthcare appear similar to those reported in other jurisdictions. Indigenous peoples facing multiple dimensions of disadvantage, especially gender and social class, may be the most likely to experience racism. It is likely that the experience of racism in healthcare has implications for Indigenous peoples' health, mainly by reducing healthcare access.
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 | 0.015 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.037 | 0.053 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".