Critical review of the role of PPE in the prevention of risks related to agricultural pesticide use
Bibliographic record
Abstract
Personal protection equipment (PPE) holds a privileged position in safety interventions in many countries, despite the fact that they should only be used as a last resort. This is even more paradoxical because many concerns have arisen as to their actual effectiveness under working conditions and their ability to provide the protection attributed to them by certain occupational safety strategies and marketing authorisation procedures. Are these concerns justified? This article is intended to provide an update on what we know of the issue based on a critical analysis of the literature to date. Analysis focuses on the assessment of the effectiveness of coveralls used to protect from plant protection products in OECD countries. All forms of assessment were retained: discussion of the observed effectiveness of PPE in relation to the underlying assumptions of marketing authorisation procedures, laboratory tests of equipment, practical field tests in which PPE-wearing practices were controlled and uncontrolled, analyses of the efficiency of preventive instructions based on wearing such coveralls. Findings show that recommending the use of PPE is key to the granting of marketing authorisation. Some dangerous products only get marketing authorisation because it is assumed that wearing PPE will considerably limit exposure. They would be banned if it were not for this assumption of protection. However the actual effectiveness of PPE in working conditions may be over-estimated. In addition many factors (cost, availability, thermic and mechanical discomfort) may make instructions to wear PPE inapplicable. Advising the use of PPE does not always mean effective protection.
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 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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".