O-311 THE CONTRIBUTION OF WORK ACTIVITY ANALYSIS IN ASSESSING THE COMFORT OF PROTECTIVE CLOTHING AGAINST PESTICIDES
Bibliographic record
Abstract
Abstract Introduction Farmers are exposed to pesticides during handling or other tasks. In Canada, due to the lack of a clear designation, a variety of clothing offering protection against pesticides are used. One of the aims of the ISO 27 065 standard is to standardize the characteristics of protective clothing (PC) in order to provide better protection for farmers. Methods A multidisciplinary research project has been developed in order to facilitate the identification of effective PC and improve farmers’ compliance with the requirements of the Pest Management Regulatory Agency (PMRA). It aims to develop a multidisciplinary methodology for evaluating the comfort of VPs dedicated to pesticides, in order to compare ISO 27 065 CP with the protective clothing currently worn by Canadian farmers. This presentation aims to demonstrate the relevance of work activity analysis, as used in ergonomics, in assessing the comfort of PC. Results The project was conducted in collaboration with Canadian 11 apple growers, all of whom were responsible for pesticide spraying in their orchards. Preliminary interviews to describe the participants’ socio-demographic profile and their use of pesticides and protective clothing were conducted prior to the spraying season. Filmed observations, coupled with measurement of external skin exposure, were carried out with the apple growers during the pesticide spray preparation-filling and spraying tasks. Thematic analysis of the verbatim and videos documented the components of comfort. Discussion The data obtained through work activity analysis thus complemented exposure measurement and questionnaire data collection. Conclusion This approach should be used to enrich proposals for task-specific design criteria.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".