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Record W6982601230

Involking silvern voices in healthcare : transforming practice by engaging older adults in collaborative partnerships

2014· article· en· W6982601230 on OpenAlexaboutno aff

Bibliographic record

VenueArca (British Columbia Electronic Library Network) · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicAutobiographical and Biographical Writing
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipHealth careEquity (law)Action (physics)Work (physics)Theme (computing)Quality (philosophy)PopulationInformation sharingPopulation ageing
DOInot available

Abstract

fetched live from OpenAlex

Canada's population is aging. This growing trend will ultimately have an impact on nursing practice as older individuals continue to seek healthcare services. Nurses must be able to work in collaboration with the older population to provide quality care. This action research study explored participative healthcare from an older adult's perspective.\n\nThis study revealed that older adults prefer to be active participants in their care. The major theme that emerged was true partnership. Three sub-themes that emerged were communication, respect, and trust. These three sub-themes work in unity to contribute to a healthcare experience that exemplifies true partnerships. This study proposes a definition of true partnership as being open to and inviting mutual communication in an atmosphere that encourages equity sharing of information contributing to respect and the development of trust that results in confident collaboration in 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 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)0.012
metaresearch head score (Gemma)0.016
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 score0.126
Threshold uncertainty score0.251

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0200.020
Scholarly communication0.0140.008
Open science0.0010.015
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.006
GPT teacher head0.191
Teacher spread0.185 · 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
Published2014
Admission routes1
Has abstractyes

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