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Record W2157547678 · doi:10.1002/nur.20242

Pursuing common agendas: A collaborative model for knowledge translation between research and practice in clinical settings

2008· review· en· W2157547678 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueResearch in Nursing & Health · 2008
Typereview
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsMichael Smith Health Research BCVancouver Coastal HealthTrinity Western UniversityWestern UniversityUniversity of British Columbia
Fundersnot available
KeywordsKnowledge translationNegotiationKnowledge managementKnowledge transferCitizen journalismParticipatory action researchHealth careProcess (computing)PoliticsSociologyComputer sciencePolitical scienceWorld Wide WebSocial science

Abstract

fetched live from OpenAlex

There is an emerging discourse of knowledge translation that advocates a shift away from unidirectional research utilization and evidence-based practice models toward more interactive models of knowledge transfer. In this paper, we describe how our participatory approach to knowledge translation developed during an ongoing program of research concerning equitable care for diverse populations. At the core of our approach is a collaborative relationship between researchers and practitioners, which underpins the knowledge translation cycle, and occurs simultaneously with data collection/analysis/synthesis. We discuss lessons learned including: the complexities of translating knowledge within the political landscape of healthcare delivery, the need to negotiate the agendas of researchers and practitioners in a collaborative approach, and the kinds of resources needed to support this process.

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.

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)0.162
metaresearch head score (Gemma)0.034
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.890
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1620.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0040.007
Science and technology studies0.0040.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.010
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 head0.968
GPT teacher head0.858
Teacher spread0.110 · 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