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Record W1749395912

The role of knowledge transfer in participatory ergonomics: evaluation of a case study at a poultry processing plant

2008· dissertation· en· W1749395912 on OpenAlexaboutno aff
David M. Antle

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2008
Typedissertation
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsEngineeringGeneral partnershipTrainerKnowledge transferParticipatory ergonomicsProductivityParticipatory action researchMedical educationEngineering managementOperations managementKnowledge managementHuman factors and ergonomicsBusinessMedicineComputer sciencePoison controlEnvironmental healthSociology
DOInot available

Abstract

fetched live from OpenAlex

Aims: -- This project involved the evaluation of a transfer of a ‘train-the-trainer’ knife sharpening and steeling program (KSP) for butchery operations from Quebec to Newfoundland. The objectives of this study were to evaluate: 1) the factors that impacted upon the transfer of the KSP from a Quebec Research Team (QRT) to the Newfoundland Research Team (NRT) and a poultry plant, 2) to evaluate the impact of the KSP on employee health and productivity and, 3) to attempt to identify the impact that a KT strategy has within a participatory ergonomics (PE) intervention. The Eastern Canadian Consortium on Workplace Health identified the KSP as a successful existing program that could be transferred to Newfoundland and Labrador. It was thought that this program would benefit a St. John's, Newfoundland poultry processing plant. Researchers (ergonomists, engineers and KT specialists), plant management and plant employees constituted a tripartite partnership that would guide the knowledge adaptation, transfer and assimilation. The KSP uses a 'train-the-trainer' approach that identified plant personnel who could acquire the ability to machine-sharpen knives. Following a series of training sessions, the plant trainers were asked, in cooperation with factory management, to proceed with training of plant workers in proper knife steeling and care techniques. The QRT provided the NRT with methods to assess skill development and work behavior changes of a production line cohort. Researchers adapted survey, video and semi-structured interview techniques to assess the intervention. A KT Model (Parent et al., 2007) was employed as a diagnostic tool to evaluate KT capacities. While KT was slow and was not completely successful, the project recognizes that KT capacities within social networks impacted on the KSP intervention. Networks for actor communications, managerial involvement, organizational culture and facilitative ability of the NRT appear to have impacted disseminative and absorptive capacities required for successful KT. The QRT and the trainers displayed active generative capacity, by developing new knowledge regarding the KSP process, and strategies to use in smaller enterprises. The NRT gained experience in applying a PE framework. However, it is clear that additional steps are required for the knowledge gained within the province from the experience to become institutionalized. At the industrial site, the trainer's skills and knowledge have been recognized as exceptional by the QRT and Quebec experts. Some, but not all, employees have adopted the principles of the KSP and demonstrate the potential for reductions in cutting-related musculoskeletal disorders. However, managers at the plant did not taken steps to institutionalize knowledge, suggesting that the continuity of the KSP may be threatened.

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)0.033
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0100.005
Scholarly communication0.0040.002
Open science0.0030.005
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.052
GPT teacher head0.331
Teacher spread0.279 · 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 designQualitative
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".

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Citations0
Published2008
Admission routes1
Has abstractyes

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