Access to Cardiovascular Care for Indigenous Peoples in Canada: A Rapid Review
Bibliographic record
Abstract
Indigenous peoples in Canada are at an increased risk of cardiovascular disease compared to non-Indigenous people. Contributing factors include historical oppression, racism, healthcare biases, and disparities in terms of the social determinants of health. Access to and inequity in cardiovascular care for Indigenous peoples in Canada remain poorly studied and understood. A rapid review of the literature was performed using the PubMed/MEDLINE, Web of Science, and Indigenous Studies Portal (iPortal) databases to identify articles describing access to cardiovascular care for Indigenous peoples in Canada between 2002 and 2021. Included articles were presented narratively in the context of delays in seeking, reaching, or receiving care, or as disparities in cardiovascular outcomes, and were assessed for their successful engagement in indigenous health research using a preexisting framework. Current research suggests that gaps most prominently present as delays in receiving care and as poorer long-term outcomes. The literature is concentrated in Alberta, Manitoba, and Ontario, as well as among First Nations people, and is largely rooted in a biomedical worldview. Additional community-driven research is required to better elucidate the gaps in access to holistic cardiovascular care for Indigenous peoples in Canada. Healthcare professionals, researchers, and policymakers should reflect further upon their actions and privilege, educate themselves about historical facts and the Truth and Reconciliation Commission, tackle prevailing disparities and systemic barriers in the healthcare systems, and develop culturally safe and ethically appropriate healthcare interventions to improve the health of all Indigenous peoples in Canada.
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 | 0.008 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.029 | 0.041 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".