P-114 IDENTIFICATION OF QUESTIONS CHARACTERIZING WORKERS’ SOCIO-TECHNICAL AND ORGANIZATIONAL LEEWAYS
Bibliographic record
Abstract
Abstract Introduction Insufficient socio-technical and organizational leeways (STOL) are considered as a risk factor for musculoskeletal disorders (MSD) in the ergonomic literature. However, no epidemiological study has investigated this concept. The aim was to identify proxy questions indicating the dimensions of STOL (macro-dimensions of operational leeway in the work situation) available in the work environment and perceived by workers in order to include them in epidemiological occupational health questionnaires. Methods The Technique for Research of Information by Animation of a Group of Experts (TRIAGE) was implemented to select questions. Seventy-five questions from French epidemiological questionnaires close to the concept of STOL were identified by an interdisciplinary working group (statistics, ergonomics, epidemiology, occupational medicine). An individual consultation and a group consultation phases followed one another. Twelve experts were solicited individually to express their agreement level, via an online questionnaire, to consider the questions as proxy of STOL. Questions not retained were discussed collectively in two online meetings between the nine experts available, and experts voted via an anonymous online questionnaire to retain (or not) each question. Results In total, 42 questions were retained as proxy of STOL: 23 in the individual consultation phase (agreement >83,3%) and 19 in the group consultation phase (agreement >85,7%). The proxy questions will be presented at the congress. Discussion To our knowledge, there is no epidemiological study on the association between STOL and MSD while this concept would be of relevance for MSD prevention. Conclusion The proxy questions could be useful for epidemiological research and for ergonomic interventions.
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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 | 0.010 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
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".