Bibliographic record
Abstract
Data from the Canadian Labour Force Survey (1997) reveal that relatively few mid-life women offer ill health as a reason for leaving their job or downshifting to part-time employment, implying that the role of ill health may be inconsequential in effecting changing patterns in mid-life women's labour force activity. In contrast, interviews with 30 mid-life women (aged 40 to 54 years) illustrate that, although they do not offer illness as their main reason for leaving their job or working part-time, health is a determining factor. This research also maps the complex relationship between work and ill health, showing that stressful working conditions (due to funding cuts and policy changes) affected the mental and physical health of this group of mid-life women, which, in turn, influenced their decision to change their labour force activity. The author concludes that policy makers must recognize that ill health may be under-reported among mid-life women in large surveys and that research is needed that specifically examines women's working conditions as they relate to health. Such research should not be based solely on large surveys but must also include qualitative studies that capture women's experiences.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".