Utilizing feminist theories when working with older adults in acute care: social workers' perspectives
Bibliographic record
Abstract
Social workers frequently engage with older adult patients when working in an acute care\nhospital setting. In order to be effective in their work, each social worker must be informed by\nand utilize one or more theoretical frameworks in their practice with each patient. One of the\ntheoretical frameworks that can be used when working with older adult patients is feminist social\nwork theory. Utilizing both a feminist and a post-modernist lens, this study looks at how feminist\nsocial work theory is applied when working with older adult patients in acute care. In order to do\nso, five acute care social workers who utilized feminist theory in their practice were interviewed\nin order to gain their perspectives on when they apply feminist theory and how they find it\nbeneficial for their patients. Themes that were developed from the interviews include:\nquestioning society-created presumptions due to one’s gender and age, understanding the\nnegative effect of the power imbalances between the patient and other involved parties, and\nencouraging both patient and social worker resilience to oppression. The themes that emerged\nfrom the interviews demonstrate how these social workers believe feminist theory is best utilized\nin their practice and when it has been found to be most effective.
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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 | 0.028 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.026 | 0.036 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.007 |
| 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".