Bibliographic record
Abstract
Contemporary social policy compels seniors who require assistance with personal or household tasks to obtain help from 'the community'---a term that most often means 'women' family members. Much is written about 'caregiver burden' but little research explores the experiences of older women who are the recipients of home care. Using narrative inquiry methodology and a life history framework, a senior woman home care recipient on Prince Edward Island, Canada, was interviewed over a span of 4 months in 2005 creating a total of 10 hours of audio taped interviews. Interviews were analysed using a critical inquiry approach embodying a feminist and political economy perspective. Data were analysed throughout the interview process and understandings emerged about how care and care needs were negotiated and managed. Exploring Aronson's (2000) 3 images available to older women, this research seeks to expand on the image of 'managing'---resistance to 'being managed'---and extend the notion of 'work' involved in staying in charge of everyday life. Work is examined under 3 concepts, managing, controlling, and raging. Social policy with its reliance on family as care givers is an inadequate response that entraps and marginalizes women both as caregivers and as care recipients. Care recipients engage in work that involves resistance and raging against injustice in their daily practice of negotiating homecare. Rage as resistance is an appropriate response to the experience of marginalization and silencing among older women care recipients. Angry seniors is an image that claims rage as a legitimate force; it is an image of older women that calls for reconstruction and research to uncover its legitimate power in the daily lives of care recipients.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.027 | 0.007 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".