The Growing Epidemic of Diabetes Among the Indigenous Population of Canada: A Systematic Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Diabetes is one of the most well-known and well-researched non-communicable diseases known to humankind. The goal of this article is to show that the prevalence of diabetes is constantly increasing among indigenous people, a major population subgroup in Canada. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used to conduct this systematic review, and the databases used were PubMed and Google Scholar. Studies that were published in the last 15 years (2007-2022) were selected for this review, and after applying the inclusion and exclusion criteria, screening, and removing duplicates, 10 articles were selected for the final review - three qualitative studies, three observational studies, and four studies without a specified methodology. We used the JBI (Joanna Briggs Institute) checklist, NOS (Newcastle-Ottawa Scale) checklist, and SANRA (Scale for the Assessment of Narrative Review) checklist for quality assessment. We found that all the articles showed that the prevalence of diabetes is increasing in all the Aboriginal communities despite all the interventional programs already in place. Rigorous health plans, health education, and wellness clinics for primary prevention can all be effective in reducing the potential risks of diabetes. More studies exploring the prevalence, effects, and outcomes of diabetes in the indigenous population of Canada are needed to effectively understand the disease and its complications in this group.
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.
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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 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 it