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Record W2005155050 · doi:10.1002/chp.20124

Knowledge Translation Research: The Science of Moving Research Into Policy and Practice

2011· review· en· W2005155050 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

VenueJournal of Continuing Education in the Health Professions · 2011
Typereview
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsKnowledge translationScope (computer science)Knowledge baseKnowledge managementHealth careSociology of scientific knowledgeEngineering ethicsReflection (computer programming)Medical educationSociologyMedicinePolitical scienceComputer scienceEngineeringSocial science

Abstract

fetched live from OpenAlex

Research findings will not change health outcomes unless health care organizations, systems, and professionals adopt them in practice. Knowledge translation research is the scientific study of the methods to promote the uptake of research findings by patients, health care providers, managers, and policy makers. Many forms of enquiry addressing different questions are needed to develop the evidence base for knowledge translation. In this paper we will present a description of the broad scope of knowledge translation research with a reflection on activities needed to further develop the science of knowledge translation. Consideration of some of the shared research challenges facing the fields of knowledge translation and continuing professional development will also be presented.

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)0.218
metaresearch head score (Gemma)0.075
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, 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 score0.714
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2180.075
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.008
Science and technology studies0.0050.002
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.008
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 head0.742
GPT teacher head0.726
Teacher spread0.016 · 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