Bibliographic record
Abstract
This synthesis paper is a review of 45 gender-sensitive studies of home and community care and caregiving. It has several purposes:! to critically review and synthesize gender-sensitive research on caregiving and home and community care primarily in Canada, focusing on unpaid caregivers and recipients of care only. This means that only studies that collect data on the sex of unpaid caregivers and recipients (women and men, women only, men only) and draw conclusions as to gender differences, similarities, or gender-specific experiences are included! to place these studies in the context of health care restructuring! to identify gaps in gender-sensitive research about home and community care! to identify the policy implications of the findings about women and men care recipients and unpaid caregivers, with particular attention to the policy recommendations of these studies! to raise awareness and understanding of the need for gender-based analysis in the area of home and community care, and the need for gender-sensitive research to inform policy-making in the area of home and community care Research findings and major themes Gender-specific research findings included the following:! women are the majority of unpaid caregivers and the majority of care recipients, and as such are greatly affected by home and community care policies and practices! women and men experience different socioeconomic contexts and gender role expectations, which result in women giving more hours of unpaid care than men,
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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 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.142 | 0.041 |
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".