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Knowledge translation in the discourse of professional practice

2011· article· en· W2024600525 on OpenAlexaff
Evelyn Cornelissen, Craig Mitton, Sam Sheps

Bibliographic record

VenueInternational Journal of Evidence-Based Healthcare · 2011
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsVancouver Coastal HealthVancouver Coastal Health Research InstituteUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersDivision of Graduate Education
KeywordsKnowledge translationRealmKnowledge managementPerspective (graphical)Health carePersonal knowledge managementDomain knowledgeProcedural knowledgeMedical knowledgeKnowledge engineeringComputer sciencePsychologyMedical educationMedicineOrganizational learningPolitical scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Clients and practitioners desire up-to-date, safe and effective healthcare. Knowledge translation, a term used to describe the interchange of knowledge between its producers and users, aims to support this desire. Knowledge, and by extension knowledge translation, is subject to varying perspectives ranging from the objective truth-tested knowledge of empiricism, associated by some with academia, to knowledge in the practitioner realm. This latter knowledge is often based on multiple users' experiences and contexts, thus constructed to meet their needs. The goal of this paper is to compare and contrast knowledge and knowledge translation from empirical and constructivist perspectives. It then relates knowledge translation to professional practice discourse and concludes with thoughts on constructivist knowledge translation strategies, including practitioner-driven strategies derived from practice. For example, knowledge translation can be woven into processes to train/integrate new graduates into the healthcare system, it can be captured in practitioner-driven provision of continuing education, and/or it can be facilitated through practitioner collaboration in research via action research approaches. Regardless of the perspective taken, delivery of up-to-date, safe and effective care requires useful, relevant knowledge available when necessary and applicable to real-life issues as perceived, critically, by the knowledge end-user.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
models splitAgreement compares identical category sets and study designs across arms.

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)0.011
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.569
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.911
GPT teacher head0.743
Teacher spread0.168 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable · Theoretical or conceptual
Domainnot available
GenreEmpirical · Commentary

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

Citations21
Published2011
Admission routes1
Has abstractyes

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