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Record W2159579686 · doi:10.1186/1748-5908-4-23

A description of a knowledge broker role implemented as part of a randomized controlled trial evaluating three knowledge translation strategies

2009· article· en· W2159579686 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueImplementation Science · 2009
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of WaterlooMcMaster University
FundersOntario Ministry of Health and Long-Term CareCanadian Institutes of Health ResearchInstitut National de Santé Publique du Québec
KeywordsKnowledge translationNoveltyKnowledge managementFacilitationRandomized controlled trialHealth services researchHealth administrationMedicinePsychological interventionProcess managementPsychologyMedical educationNursingPublic healthBusinessComputer scienceSocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: A knowledge broker (KB) is a popular knowledge translation and exchange (KTE) strategy emerging in Canada to promote interaction between researchers and end users, as well as to develop capacity for evidence-informed decision making. A KB provides a link between research producers and end users by developing a mutual understanding of goals and cultures, collaborates with end users to identify issues and problems for which solutions are required, and facilitates the identification, access, assessment, interpretation, and translation of research evidence into local policy and practice. Knowledge-brokering can be carried out by individuals, groups and/or organizations, as well as entire countries. In each case, the KB is linked with a group of end users and focuses on promoting the integration of the best available evidence into policy and practice-related decisions. METHODS: A KB intervention comprised one of three KTE interventions evaluated in a randomized controlled trial. RESULTS: KB activities were classified into the following categories: initial and ongoing needs assessments; scanning the horizon; knowledge management; KTE; network development, maintenance, and facilitation; facilitation of individual capacity development in evidence informed decision making; and g) facilitation of and support for organizational change. CONCLUSION: As the KB role developed during this study, central themes that emerged as particularly important included relationship development, ongoing support, customized approaches, and opportunities for individual and organizational capacity development. The novelty of the KB role in public health provides a unique opportunity to assess the need for and reaction to the role and its associated activities. Future research should include studies to evaluate the effectiveness of KBs in different settings and among different health care professionals, and to explore the optimal preparation and training of KBs, as well as the identification of the personality characteristics most closely associated with KB effectiveness. Studies should also seek to better understand which combination of KB activities are associated with optimal evidence-informed decision making outcomes, and whether the combination changes in different settings and among different health care decision makers.

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)0.031
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.429
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0310.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.685
GPT teacher head0.704
Teacher spread0.019 · 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