Bibliographic record
Abstract
Family support groups (FSG) have been recognized as an important and viable means for responding to the needs of family caregivers. How these groups work, however, is not well understood. The purpose of this qualitative exploratory study was to explore the impact of attending a family support group on the caregiving experience from the perspective of the family member. Personal, semi-structured interviews took place with eleven family members who had participated in at least one FSG. Data was analyzed for themes, using a constant comparative categorizing strategy. This analysis suggests that attending a FSG impacts the caregiving experience in four important ways: helping the family member to construct a self-identity as a ‘caregiver’; promoting a sense of personal competence; fostering the use of formal support groups; and creating a community context within which to experience the caregiving role. Cumulatively, these have the potential to contribute to a sense of empowerment for the family member by helping him or her to reposition the caregiving experience as more than a personal issue and promoting the emergence of a more collective voice.
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 | 0.027 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".