Bibliographic record
Abstract
One in 10 Canadians (9.6%) has problems affording prescription drugs, leading them to skip doses of their medications or to decide against filling or refilling prescriptions. The findings come from a study conducted by researchers at the University of Toronto, the University of British Columbia and the Institute for Clinical Evaluative Sciences, and published in the Canadian Medical Association Journal (CMAJ) on January 16, 2012. The research found the cost barrier to be most prevalent among Canadians without drug insurance, with 26.5% reporting problems with affordability. The study was based on analysis of data from more than 5700 people in the 2007 Canadian Community Health Survey, conducted by Statistics Canada. Two-thirds of Canadian households pay out of pocket for at least some portion of their prescription drug costs. In 2010, these expenditures totalled $4.6 billion — about 17.5% of total prescription-drug spending in the country. The study also found that Canadians who reported fair or poor health status were 2.6 times more likely to avoid taking prescription medications because of cost, and those with chronic health conditions were 1.6 times more likely not to take their medicines as directed — due to cost. Provincially, those living in British Columbia were more than twice as likely to report not being able to afford their prescription drugs than those living in other large provinces.
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 | 0.004 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".