Bibliographic record
Abstract
Health Issue: Arthritis is one of the most prevalent chronic conditions in Canada and a leading cause of long-term disability, pain, and increased health care utilization.It is also a far more prevalent condition among women than men.Information was obtained primarily from the 1998-99 National Population Health Survey and the Canadian Joint Replacement Registry. Key Findings:In 1998, the overall prevalence of self-reported arthritis or rheumatism in Canadian women was 20.0%.This rate increased to 55.6% among women over 75 years of age.Compared to women with chronic conditions, women with arthritis were more likely to experience long-term disability; report worse health; experience more pain; be dependent upon others and consult general practitioners, specialists, and physiotherapists more frequently.While men and women with arthritis under-utilize total joint replacement surgery, the degree of under-use was over three times greater for women. Data Gaps and Recommendations:There is a lack of detailed information on the use of health care services by women with arthritis.There are also no systematic data available on the prescribing of medications, access to services such as assistive devices or exercise programs, or use of community support, self-management strategies, or rehabilitation services.The burden of arthritis both on women and on society is expected to increase as the population ages.A comprehensive health strategy to reduce the impact of arthritis is required to ensure that health and support services are available in a timely manner and provided in such a way to meet the needs of Canadian women.
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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.021 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.029 | 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".