Developing regional workplace health and hazard surveillance in the Americas
Bibliographic record
Abstract
An objective of the Workers' Health Program at the Pan American Health Organization (PAHO) is to strengthen surveillance in workers' health in the Region of the Americas in order to implement prevention and control strategies. To date, four phases of projects have been organized to develop multinational workplace health and hazard surveillance in the Region. Phase 1 was a workshop held in 1999 in Washington, D.C., for the purpose of developing a methodology for identifying and prioritizing the top three occupational sentinel health events to be incorporated into the surveillance systems in the Region. Three surveillance protocols were developed, one each for fatal occupational injuries, pesticide poisoning, and low back pain, which were identified in the workshop as the most important occupational health problems. Phase 2 comprised projects to disseminate the findings and recommendations of the Washington Workshop, including publications, pilot projects, software development, electronic communication, and meetings. Phase 3 was a sub-regional meeting in 2000 in Rosario, Argentina, to follow up on the progress in carrying out the recommendations of the Washington workshop and to create a Virtual Regional Center for Latin America that could coordinate the efforts of member countries. Currently phase 4 includes a number of projects to achieve the objectives of this Center, such as pilot projects, capacity building, editing a compact disk, analyzing legal systems and intervention strategies, software training, and developing an internet course on surveillance. By documenting the joint efforts made to initiate and develop Regional multinational surveillance of occupational injuries and diseases in the Americas, this paper aims to provide experience and guidance for others wishing to initiate and develop regional multinational surveillance for other diseases or in other regions.
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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 | 0.020 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".