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Record W4232840163 · doi:10.24124/2020/59133

Long journeys: Healthcare providers’ perspectives about promoting equity and community-based palliative care for rural, remote, and indigenous communities in northern British Columbia.

2020· dissertation· en· W4232840163 on OpenAlexaffabout
Kimberley Anh Thomas

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPalliative careIndigenousNursingEquity (law)Health careHealth equityQualitative researchMedicinePublic healthSociologyPolitical science

Abstract

fetched live from OpenAlex

Inequitable access to palliative care in Canada is a pressing issue. People with life-limiting illnesses in rural and remote northern and Indigenous geographies in British Columbia (BC) face ethically problematic barriers to receiving palliative care. Palliative approaches that are equity-oriented and community-based bring significant improvements to the healthcare system and to people's quality of life. The purpose of this qualitative study was to find ways to promote health equity and community-based palliative care. This research is informed by action-oriented, anti-colonial, and critical Indigenous methodologies. As perspectives of frontline healthcare workers offer transformative insights, palliative care providers working in northern BC were interviewed, and, from their interviews, three main themes emerged. These were (1) Support Primary Palliative Care, (2) earlier and inclusive Integration of Palliative care, and (3) Culturally Safe Palliative Care. The implications of these findings are situated at the intersection of cultural safety, public health, and health promotion.

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 imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score0.935

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.010
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0360.013
Scholarly communication0.0090.003
Open science0.0020.006
Research integrity0.0030.010
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.116
GPT teacher head0.415
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes2
Has abstractyes

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