Ergonomic Work Analysis, Training and Action: New Paths Opened by the Interconnection of Approaches
Bibliographic record
Abstract
The work presented since 1991 (Paris) at the Symposiums of the IEA Congresses specialized in the theme “ Ergonomic work analysis and training” has demonstrated the main development lines of the place of training in and by work analysis in the practices and theoretical problematics of ergonomists and other work professionals. There is a progressive integration of concepts, objectives and intervention fields (training of work actors, professional training) which were distinguished in the past. New paths are opening up. In a participatory approach, these new paths are being used to organize training and action in work environments as well as individual and collective development. In particular, interdisciplinarity is helping this development while enabling ergonomists to obtain a clearer identification of their originality. The risks of the failure of an action and the conditions for its success are also being more clearly defined.
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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 | 0.055 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.008 | 0.117 |
| Scholarly communication | 0.035 | 0.063 |
| Open science | 0.003 | 0.024 |
| Research integrity | 0.008 | 0.015 |
| Insufficient payload (model declined to judge) | 0.005 | 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".