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Record W2137531287 · doi:10.1177/1075547003252334

Sustained, Intensive Engagement to Promote Health and Safety Knowledge Transfer to and Utilization by Workplaces

2003· article· en· W2137531287 on OpenAlexaff
Desré M. Kramer, Donald C. Cole

Bibliographic record

VenueScience Communication · 2003
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsUniversity of TorontoInstitute for Work & Health
Fundersnot available
KeywordsKnowledge transferKnowledge managementIntervention (counseling)Body of knowledgeProcess (computing)BusinessPsychologyComputer science

Abstract

fetched live from OpenAlex

The need to establish a positive relationship between the source of the knowledge and the user organization to achieve knowledge utilization is an established principle of knowledge transfer. Yet, the process of establishing such a relationship and its impact on knowledge utilization remains relatively unexplored in the field of workplace health and safety. This article describes such a knowledge transfer intervention with three manufacturing workplaces. Using qualitative methods, a knowledge broker documents and evaluates a knowledge transfer intervention and the utilization of a body of research on workplace health and safety. This article explores the issues of intensity, duration, and the interactive nature of positive relationship building and highlights the implications for knowledge transfer on workplace 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)0.006
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.147
GPT teacher head0.506
Teacher spread0.358 · 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.

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

Citations72
Published2003
Admission routes1
Has abstractyes

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