Bibliographic record
Abstract
This paper addresses age differences in women's perceptions of their health problems and concerns. The data are drawn from interviews with a stratified random sample of 356 women in Hamilton, Canada. The data show that women of all ages are concerned or worried about the major causes of death including heart disease, all types of cancer and road traffic accidents although younger women are more concerned with breast cancer and cancer of the womb. In terms of the health problems they have experienced, while stress and tiredness are common health problems reported by women of all ages, older women are more likely than the younger women to report life threatening health problems such as heart disease, lung disease and chronic diseases such as arthritis and osteoporosis. Information from in-depth interviews with 32 of the women reveal that the sources of stress, tiredness and depression lie in the social context of women's lives and differ for women of different ages. The authors conclude that it should not be assumed that women's health concerns and experiences are homogeneous. In research on women's health and in shaping women's health policy, it is important to recognize that there are fundamental differences between women of different ages.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.842 | 0.520 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".