Bibliographic record
Abstract
Many people have grave concerns that Canadian taxpayers have not received value for the time, energy and money spent on analysis of our healthcare system over the last 20 years. The number of reports and recommendations is enormous. Millions of dollars have been spent. While we have been busy studying healthcare costs, they have risen. How can Canadians judge if we have received our money's worth : Some criteria are: there would be greater clarity regarding the goals of healthcare system reform; citizens would understand the issues better; federal-political "wrangling" would be closer to resolution; agreement on long-overdue efficiencies would result in obvious improvement; major disagreements about the way forward would also be clearly understood; and finally, accountability to Canadians for acting on healthcare recommendations would be a reality.
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 | 0.014 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.010 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.044 | 0.033 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".