The Canadian Rx atlas, 2nd edition
Bibliographic record
Abstract
"Canadian governments, employers, unions, and patients currently spend more money on prescription drugs (about $20 billion in 2007) than is spent on all services provided by physicians in Canada. At the same time, prescription drug spending per capita varies by over 50% across provinces. Surprisingly little information is systematically collected to determine which drugs account for most of the spending in Canada, what factors drive interprovincial variations in spending, and whether population age is an important cause of spending variations across provinces and trends over time. The 2nd edition of The Canadian Rx Atlas significantly enhances our understanding of medicine use by providing the first-ever portrait of age-specific patterns of prescription drug use and costs across provinces. It breaks down nearly $20 billion in prescription drug spending (private and public) and provides a comprehensive portrait of the factors that drive trends over time and variations across provinces." -CHSPR website
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.023 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.159 | 0.066 |
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".