Chronic Healthcare Spending Disease: A Macro Diagnosis and Prognosis
Bibliographic record
Abstract
The amount Canadians spend on healthcare is set to rise rapidly over the next two decades and Canadians need to face up to tough choices to deal with this “spending disease.” The study examines the trajectory of total healthcare spending – public and private – in Canada and the policy choices Canadians must make in response. The authors estimate the extent to which healthcare spending is going to absorb a greater fraction of income than Canadians have experienced to date under two scenarios: a baseline scenario drawn from historical experience, and an optimistic scenario, which assumes an unprecedented improvement in the efficiency and effectiveness of the healthcare system and large improvement in potential economic growth. Canadians must choose some combination of: 1) a sharp reduction in public services, other than health care; 2) increased taxes to finance the public share of healthcare spending; 3) increased individual spending on healthcare services currently insured by provinces, through some form of co-payment or through delisting of services that are currently publicly financed; 4) or a degradation of publicly insured healthcare standards – longer queues, and services of poorer quality.
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 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".