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Record W4231495080 · doi:10.24124/2018/58872

Public health nurses' experience of collaboration with primary care providers in northern British Columbia

2018· dissertation· en· W4231495080 on OpenAlexaffabout
Sara Pyke

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsNursingTeamworkPrimary careAutonomyHealth carePublic healthPublic health nursingPrimary health careMedicineFamily medicinePolitical science

Abstract

fetched live from OpenAlex

Public health nurses (PHNs) and primary care providers in northern British Columbia will need to work closely together in primary care homes and interprofessional teams, but little is known about how these providers collaborate. In this study, fifteen PHNs shared their experiences of collaborating with primary care providers in day-to-day practice. Interpretive description methods of analysis (Thorne, 2008) revealed that PHNs’ experience of collaboration was characterized by the themes of power, autonomy, communication, and a public health perspective. PHNs viewed collaboration with primary care providers somewhat skeptically, but they possessed the knowledge, skills, and abilities to collaborate successfully. The facilitators of collaboration were client-centred care, professional relationships, teamwork, leadership, and direct communication. When PHNs made clients’ needs and preferences for care and services their priority, the foundational aspects of collaboration were expressed in their practice, and collaboration with primary care providers contributed to positive outcomes for clients, families, and communities.

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)0.003
metaresearch head score (Gemma)0.008
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 score0.779
Threshold uncertainty score0.444

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0220.006
Scholarly communication0.0050.001
Open science0.0020.006
Research integrity0.0020.003
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 head0.024
GPT teacher head0.395
Teacher spread0.371 · 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
Published2018
Admission routes2
Has abstractyes

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