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Record W2260282987

Community capacity building in palliative care: An illustrative case study in rural Northwestern Ontario

2013· article· en· W2260282987 on OpenAlexaffvenueabout
Mary Lou Kelley, Lily DeMiglio, Allison Williams, Jeanette Eby, Michele McIntosh

Bibliographic record

VenueJournal of rural and community development · 2013
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsTrent UniversityMcMaster UniversityLakehead University
Fundersnot available
KeywordsPalliative careNursingParticipatory action researchRural areaCitizen journalismAction researchMedicineNeeds assessmentCapacity buildingRural healthPsychologySociologyEconomic growthPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Despite the increasing need for palliative care, it is well recognized that people who are dying in rural and remote areas have less access to palliative care services than their urban counterparts. Barriers to accessing palliative care for rural residents include geographic isolation, shortage of human resources, and lack of palliative care education and training for rural health care providers. Community capacity development has become an accepted practice approach to developing rural health services, essentially 'building on what already exists'. This case study research conducted in northwestern Ontario, Canada, examined the application of a four phase community capacity development model as an intervention to develop a palliative care program in a rural community. Data were collected over the three-year period using a participatory action research approach. Findings illustrated the applicability of the model to guide rural palliative care development and provided details of the community change process. Conclusions support the applicability of the model for use as a theory of change to guide and evaluate rural palliative care service development. Keywords: rural health, rural palliative care, palliative care, community capacity development, participatory action research, rural health teamwork, end-of-life care.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.260
Threshold uncertainty score0.953

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.166
GPT teacher head0.381
Teacher spread0.216 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2013
Admission routes3
Has abstractyes

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