Analysis of the Difficulties Encountered by the Participants in a Participatory Ergonomic Process
Bibliographic record
Abstract
This communication discusses the difficulties encountered by an ergonomics group's participants in two different plants in an ergonomic analysis of varied tasks. During work meetings attended by the ergonomists, the two ergonomics groups analyzed three jobs using an analysis tool developed by the researchers. The participants' difficulties were identified from an analysis of the content of the ergonomists' interventions during the meetings. The results obtained from the analysis of the second job revealed significant differences between the two plants. In plant 1, the participants' difficulties were expected learning-related difficulties, while in plant 2, the difficulties were unexpected and major. In this latter plant, most of the ergonomists' interventions were integrated into discussion cycles and were related to high intensity difficulties. The results indicate that the participants had difficulties that related to their representation of the basic concepts and objectives of ergonomics; they also had difficulty detailing the solutions and did not recognize the benefit of collaborating with company engineers. The results suggest that ergonomics committees' learning is related to company culture and establishes the limits of the ergonomist's role when he fails to change the participants' representations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.046 | 0.095 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".