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Record W2910673297 · doi:10.1080/14773996.2018.1508116

Knowledge transfer and exchange in health and safety: a rapid review

2019· review· en· W2910673297 on OpenAlexafffund
Dwayne Van Eerd

Bibliographic record

VenuePolicy and Practice in Health and Safety · 2019
Typereview
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsInstitute for Work & Health
FundersWorkplace Safety and Insurance Board
KeywordsJurisdictionOccupational safety and healthKnowledge transferComputer scienceMedicineKnowledge managementPolitical scienceLaw

Abstract

fetched live from OpenAlex

Workplace injury and illness can be burdensome for workers and workplaces regardless of jurisdiction. The notion of research to practice is important in health and safety research. The objective of this article is to describe and synthesize the literature describing knowledge transfer and exchange (KTE) approaches relevant to workplaces. A rapid review of the literature was done. Search strategies were run in eight electronic databases. Documents describing a KTE approach for workplaces were reviewed. Data related to key aspects of the KTE approach as well as conceptual guidance were extracted and synthesized. Literature searches revealed 34 documents that described 23 different KTE approaches designed to reach workplace audiences. Many KTE approaches were guided by conceptual frameworks. Common elements related to audience, activities and impact were found to guide future KTE approaches. Including workplace parties as an audience in a multi-faceted approach are important principles of KTE for health and safety.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0140.016
Science and technology studies0.0010.001
Scholarly communication0.0050.006
Open science0.0020.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.338
GPT teacher head0.594
Teacher spread0.256 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designSystematic review
DomainMethods
GenreReview

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

Citations28
Published2019
Admission routes2
Has abstractyes

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