Applying feminist, multicultural, and social justice theory to diverse women who function as caregivers in end-of-life and palliative home care
Bibliographic record
Abstract
OBJECTIVE: Women are largely responsible for providing care to terminally ill family members at home. The goal of this review is to conceptualize diverse women's experiences in palliative home care from feminist, multicultural, and social justice perspectives. METHODS: Peer-reviewed manuscripts were identified using the following databases: CIMAHL, psycINFO, and pubMED. The following search terms were used: women/mothers/daughters, Caregiving, family caregivers, feminism, culture, multiculturalism, and palliative home care. Article reference lists were also reviewed. The majority of penitent articles which formed the basis for the arguments presented were drawn from nursing, medicine, and counseling psychology scholarship. RESULTS: The application of feminist, multicultural, and social justice theory brings to attention several potential issues female caregivers may experience. First, there exist diverse ways in which women's Caregiving is manifested that tend to correspond with variations in culture, relationship, and age. Second, it is important to attend to changing expectations placed on women as a result of Caregiving at the end of life. Third, the changing power dynamics women may experience in end of life Caregiving are very complex. SIGNIFICANCE OF RESULTS: The principle finding of the review was the highlighting of potential risks that culturally diverse female caregivers are likely to face at the end of life. The application of social justice theory provides a number of implications for practice and policy. Specifically, the identifying significant concerns regarding female caregivers in palliative home care, as well as suggesting ways to appropriately attend to these concerns, and oppression of women is less likely to be perpetuated, specific areas for future research in this domain are identified.
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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 | 0.021 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".