A Guaranteed Annual Income Benefits the Health of Canadians with Chronic Illness
Bibliographic record
Abstract
Chronic illness is currently the number one cause of death in Canada and the largest cost to our increasingly unsustainable healthcare system. Unfortunately, the massive fiscal and social cost of chronic illness is only expected to get worse as the Canadian population ages. Economists, researchers and politicians across Canada have suggested that novel approaches to health and wellness are required to reduce the rate of chronic illness in Canadian populations. One of these novel approaches is alleviating poverty through a guaranteed Annual Income (GAI). For over forty years, the concept of a guaranteed annual income has been part of welfare discussions in Canada. Canadian research has suggested that a guaranteed income can reduce the cost of healthcare by addressing income security and poverty as upstream determinant of health. By manipulating extracted data from the Canadian Community Health Survey, this study also provides evidence that a guaranteed income is an effective healthcare innovation that warrants further research. This study concludes that a GAI policy is worth investigating as it can help alleviate poverty and the burden of chronic illness in Canada.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".