Bibliographic record
Abstract
Population aging and longevity due to medical advances over the past few decades have meant that the approximately 44 million caregivers in the United States and eight million caregivers in Canada must provide more intensive levels of care and for longer periods of time. Consequently, caregivers are often profoundly affected by their caregiving role in emotional, psychological, physical, and financial ways. Thirty years of research on this population have helped to create a caregiver profile and identify the significant challenges for caregivers. One area explored to a much lesser extent is the postcaregiving period, when the caregiver transitions into a period of bereavement. This period can be particularly challenging for caregivers given the commitment inherent in the caregiving process. Research has shown that the emotional reactions of caregivers as well as practical challenges do not end with the death of the care recipient. In fact, complex realities, tensions, and responses continue well after the death into the postcaregiving period. This study of bereaved women caregivers explored their lived experiences in the postcaregiving phase. One central theme emerged and suggested that the experience of caregiving had an effect on the caregivers' identities, which then influenced their bereavement processes and experiences.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.003 |
| 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".