Bibliographic record
Abstract
Provincial spending on health care increased for the fourth straight year in 2000, after 5 years of low growth or declining expenditures. Preliminary provincial and territorial health spending data released by the Canadian Institute for Health Information show that the amount spent on health care reached $59 billion in 1999, accounting for just over 35% of all provincial government spending. That is expected to have climbed to 37% during 2001. Health care spending as a percentage of provincial gross domestic product (GDP) was relatively stable during the late 1990s, at about 6%. The Atlantic provinces and Manitoba, which tend to have lower GDPs than the other provinces, spent a greater proportion — 8; to 9% of GDP — on health care. During the period of minimal growth in total spending on health care that lasted from 1992 to 1996, per capita expenditures declined from $1708 to $1648, or by 3.5;. More recently, per capita spending increased to $1932 in 1999 and is expected to reach $2229 in 2001. After adjusting for inflation, this translates to a 26% increase since 1996. However, the higher 2001 figures represent only a 16% increase from per capita spending levels set in 1991. By 2001, all provinces are expected to have showed gains in adjusted (real) per capita spending over the levels of a decade earlier. If this occurs, Newfoundland will see the biggest increase (49%) followed by Manitoba at 34% and New Brunswick at 30%. Alberta has more than recovered from its period of decline during the first half of the 1990s, posting an spending increase of 58% since 1995.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.051 | 0.031 |
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".