Caregiving at the margins: An ethnographic exploration of family caregivers experiences providing care for structurally vulnerable populations at the end-of-life
Bibliographic record
Abstract
BACKGROUND: People experiencing structural vulnerability (e.g. homelessness, poverty, racism, criminalization of illicit drug use and mental health stigma) face significant barriers to accessing care at the end-of-life. 'Family' caregivers have the potential to play critical roles in providing care to these populations, yet little is known regarding 'who' caregivers are in this context and what their experiences may be. AIM: To describe family caregiving in the context of structural vulnerability, to understand who these caregivers are, and the unique challenges, burdens and barriers they face. DESIGN: Critical ethnography. SETTING/PARTICIPANTS: Twenty-five family caregivers participated. Observational fieldnotes and semi-structured interviews were conducted in home, shelter, transitional housing, clinic, hospital, palliative care unit, community-based service centre and outdoor settings. RESULTS: Family caregivers were found to be living within the constraints of structural vulnerability themselves, with almost half being street family or friends. The type of care provided varied greatly and included tasks associated with meeting the needs of basic survival (e.g. finding food and shelter). Thematic analysis revealed three core themes regarding experiences: Caregiving in the context of (1) poverty and substance use; (2) housing instability and (3) challenging relationships. CONCLUSION: Findings offer novel insight into the experiences of family caregiving in the context of structural vulnerability. Engaging with family caregivers emerged as a missing and necessary palliative care practice, confirming the need to re-evaluate palliative care models and acknowledge issues of trust to create culturally relevant approaches for successful interventions. More research examining how 'family' is defined in this context is needed.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.006 |
| 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".