Improving Palliative Care Services in a BC First Nation
Bibliographic record
Abstract
A BC First Nation has been able to come up with innovative solutions to address the increased healthcare demands such as improving high speed internet access to facilitate access to telehealth. However, there are still significant barriers that remain that make it difficult for the community to provide its surging palliative care population with optimal care. Indigenous patients already experience unique social, cultural and economic barriers to accessing quality healthcare, including palliative care. The modern day effects of colonialism, Indian hospitals, and residential schools are demonstrated through the health inequities present in Indigenous communities. Indigenous patients are more likely to have a chronic health condition such as diabetes, cancer, and have complications sooner that leads them to pursue palliative care. For many Indigenous communities, death is not just a physical process, but a social and spiritual event. As a result, significant improvements need to be made to change the course of declining palliative care services. According to our community partner, the deterioration in care is due to many factors such as communication breakdowns, lack of integration of Indigenous cultural practices and insufficient staffing support. As many of these deficiencies in care can be resolved through improved integration of the various palliative care services available within the community, our project aims to bridge the gap between the different healthcare facilities. These include the local health department, Vancouver Coastal Health (VCH) palliative care team, the pharmacy and local practitioners.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".