Report summary – Diabetes in Canada: facts and figures from a public health perspective
Bibliographic record
Abstract
"Diabetes in Canada: facts and figures from a public health perspective" is the first comprehensive diabetes surveillance report published by the Public Health Agency of Canada. The report aims to support public health professionals and organizations in developing effective, evidence-based public health policies and programs to prevent and manage diabetes and its complications. The report, developed in collaboration with provincial and territorial governments, the Canadian Diabetes Association, Juvenile Diabetes Research Foundation, CNIB, Health Canada and the academic community, uses data from national health surveys and vital statistics, as well as population-based administrative data from the Canadian Chronic Disease Surveillance System (CCDSS). For the first time, the CCDSS contains data from all 13 Canadian jurisdictions. Using CCDSS data representing cases of diagnosed diabetes among Canadians aged one year and older, Diabetes in Canada presents prevalence and incidence national rates from the fiscal year 2008/2009 and national trends from 1998/1999 onwards. The report also outlines sub-populations at higher risk, ways of reducing the risks of developing the disease and its complications, and estimates of related economic costs. In addition, it contains sections on specific populations, including children and youth and First Nations, Inuit and Métis populations.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.010 | 0.021 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".