Relationships in healthcare and homelessness: Exploring solidarity
Bibliographic record
Abstract
Background: People experiencing homelessness have some of the highest morbidity rates and lowest age of mortality in Canada yet face many barriers to care, in particular the attitudes of healthcare providers.Objectives: In this critical ethnographic study, power within client–provider relationships in health care with people experiencing homelessness is explored.Methods: Multiple qualitative methods of document analysis, participant observation, interviews, and focus groups were used with both clients and providers in a community clinic for people experiencing homelessness. Data analysis involved individual and team thematic analysis, guided by Lather's (2007, Getting lost: Feminist efforts towards a double(d) science. Albany, NY: SUNY Press) Lather, P. A. (2007). Getting lost: Feminist efforts towards a double(d) science. Albany, NY: SUNY Press. [Google Scholar] criteria for validity.Results: Caregiving relationships involve a negotiation of power based on the many differences of social location between clients and providers. Both clinic policies and personal practices influence the ways power is asserted, taken, or shared.Conclusions: In discussing the implications for addressing power relations in caregiving relationships, it is highlighted that most work in this area has focused on educating health professionals to assist them to relate in more appropriate ways. More needs to be done to actively address the power differentials inherent in caregiving with people experiencing homelessness, for which the concept of ‘solidarity’ is presented as offering some promise.
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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 | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.012 | 0.034 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.002 | 0.005 |
| 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".