Critical to care: the invisible women in health services
Bibliographic record
Abstract
Who counts as a health care worker? The question of where we draw the line between health care workers and non-health care workers is not merely a matter of academic nicety or a debate without consequences for care. It is a central issue for policy development because the definition often results in a division among workers in ways that undermine care. Critical to Care uses a wide range of evidence to reveal the contributions that those who provide personal care, who cook, clean, keep records, and do laundry make to health services. As a result of current reforms, these workers are increasingly treated as peripheral even though the research on what determines health demonstrates that their work is essential. The authors stress the invisibility and undervaluing of 'women's work' as well as the importance of context in understanding how this work is defined and treated. Through a gendered analysis, Critical to Care establishes a basis for discussing research, policy, and other actions in relation to the work of thousands of marginalized women and men every day. © University of Toronto Press Incorporated 2008.
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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.063 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".