Key Challenges for Indigenous Peoples of Canada in terms of Oral Health Provision and Utilization: A Scoping Review
Bibliographic record
Abstract
Background: The oral health of Indigenous peoples in Canada is lacking compared with their non-Indigenous counterparts. This scoping assessment aimed to investigate the obstacles of providing and using oral healthcare among Indigenous peoples in Canada. Methods: The scoping review took place between December 15, 2021 and January 10, 2022. Five key databases were examined: PubMed, Scopus, ISI Web of Science, Embase, and PROQUEST. The data were analyzed using NVIVO software to facilitate understanding of the major themes, subthemes, and codes provided. Results: Seven major themes and eighteen subthemes were identified as impacting the oral health provision and utilization of Indigenous peoples in Canada. The major themes are individual characteristics, affordability, availability, accessibility, accommodation, acceptability, and public or government policy. Thus, to improve the oral health of the Indigenous peoples in Canada, an integrated approach is required to address these obstacles. Conclusions: To address the oral health disparities among Indigenous peoples in Canada, policymakers should adopt an integrated approach.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".