Bibliographic record
Abstract
Improving the health of individuals and populations while assuring the sustainability of modern healthcare systems requires a greater commitment to chronic disease prevention and management. In Canada, national challenges in the management of health care systems, such as prolonged wait times, have benefited from targeted federal investment, with provincial and territorial collaboration in the development and implementation of local strategies. The lead paper "An Inconvenient Truth: A Sustainable Healthcare System Requires Chronic Disease Prevention and Management Transformation," makes a sound argument for a similar investment toward the epidemic of chronic disease. Any strategy that might emerge from such a federal commitment ought to recognize two fundamentally important issues. First, as chronic disease prevention and management activities are largely community-based (rather than hospital or facility-based), Canada has an opportunity to move beyond a potentially disparate collection of provincial and territorial approaches to a truly national strategy. Second, and more important, effective chronic disease prevention and management will only be achievable if we reframe the challenge as a societal issue, not simply a health system concern. This reframing exercise might benefit from a greater understanding of how societal responses to other crises, such as global warming, have been triggered or accelerated.
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 | 0.013 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.059 | 0.064 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".