Systemic Challenges, Local Solutions: Health Equity at the Intersection of Medical and Social Services Sectors
Bibliographic record
Abstract
Background: previous research highlights many barriers faced by individuals experiencing homelessness and nearing the end of life. Despite years of research examining the gaps in palliative and end-of-life care, people experiencing homelessness remain unsupported by both medical and social services systems. Objectives: this study examines health equity at the intersection of palliative and non-profit care for individuals experiencing homelessness in Calgary, Canada. We were guided by the Health Equity Framework to interpret our findings. Our aim was to identify actionable solutions within existing systems and explore strategies that can bridge silos between medical and social services. Proposed Methods: semi-structured interviews were conducted with seven service users of a mobile palliative care organization and 11 healthcare providers whose work intersected both medical and social services. Using inductive thematic analysis, supported by NVivo 14 software, we identified opportunities for promoting equitable palliative and end-of-life care. Results/Implications: three interconnected themes emerged where shifts in (1) provider attitudes, (2) governance and policy changes, and (3) improved access to resources/streamlined navigation, shaped access to care. This study emphasizes locally adaptable, equity-driven solutions, moving beyond identifying barriers to care. It also contributes to the dialogue on collaboration and inter-systemic reform to better support individuals experiencing homelessness and nearing the end of life. Our findings encourage health care professionals from social work and medical settings to come together to deliver equity-focused care and for accessible sharing and dissemination of information and resources. Keywords: palliative end of life care, health equity, homelessness, houselessness, resource navigation, community-based care
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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 | 0.013 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.019 | 0.040 |
| Scholarly communication | 0.017 | 0.009 |
| Open science | 0.002 | 0.028 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 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".