MétaCan
Menu
Back to cohort
Record W2015780697 · doi:10.3885/meo.2009.t0000142

Knowledge translation in health research: A novel approach to health sciences education

2009· article· en· W2015780697 on OpenAlexafffundabout
Sylvia Reitmanova

Bibliographic record

VenueMedical Education Online · 2009
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsMemorial University of Newfoundland
FundersCanadian Mental Health AssociationNewfoundland and Labrador Centre for Applied Health Research
KeywordsKnowledge translationGovernment (linguistics)Variety (cybernetics)Medical researchMedical educationTranslational researchInclusion (mineral)SalientPublic relationsKnowledge managementEngineering ethicsPolitical scienceMedicineSociologyComputer scienceEngineeringSocial science

Abstract

fetched live from OpenAlex

The salient role of knowledge translation process, by which knowledge is put into practice, is increasingly recognized by various research stakeholders. However, medical schools are slow in providing medical students and health professionals engaged in research with the sufficient opportunities to examine more closely the facilitators and barriers to utilization of research evidence in policymaking and implementation, or the effectiveness of their research communication strategies. Memorial University of Newfoundland now offers a knowledge translation course that equips students of community health and applied health research with the knowledge and skills necessary for conducting research, that responds more closely to the needs of their communities, and for improving the utilization of their research by a variety of research consumers. This case study illustrates how the positive research outcomes resulted from implementing the knowledge translation strategies learned in the course. Knowledge translation can be useful also in attracting more funding and support from research agencies, industry, government agencies and the public. These reasons offer a compelling rationale for the standard inclusion of knowledge translation courses in health sciences education.

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 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)0.022
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.726
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.651
GPT teacher head0.676
Teacher spread0.024 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations7
Published2009
Admission routes3
Has abstractyes

Explore more

Same venueMedical Education OnlineSame topicHealth Sciences Research and EducationFrench-language works237,207