Daughters Giving Care to Mothers Who Have Dementia: Mastering the 3 R’s of (Re)Calling, (Re)Learning, and (Re)Adjusting
Bibliographic record
Abstract
Using the process of constant comparative analysis to examine interview data, the current study explored the process of taking on and continuing to give care to mothers with dementia. The sample consisted of 19 daughters and 1 daughter-in-law; all but one were living with the mother. The core phenomenon of mastery captured the processes of (re)calling, through (re) learning how to be with the mother to (re)adjusting as the daughters try to take care of themselves and consider placing their mother in a nursing home. Through these processes, the daughters essentially deconstruct their images of their mother and rebuild the image to include the impact of the disease process. The inclusion of the cognitive work adds an additional focus for potential intervention with daughters who, in providing care for their mothers, form such a vital part of current health care systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".