SS01-01 THE SHEFFIELD GROUP AND ITS ROLE IN GLOBAL OSH RESEARCH ACTIVITIES
Bibliographic record
Abstract
Abstract Introduction In 1988, a group of directors from national health and safety research facilities agreed that there would be value in creating a global network to discuss high level issues relating to the delivery of occupational health and safety research. The group held this first meeting in Sheffield (hence the “Sheffield Group”), and the Director of the UK facility was elected as the permanent Chair in perpetuity. The original membership included national labs from Australia, Canada, Denmark, France, Hungary, Norway, Netherlands, Poland, United Kingdom, Italy, Spain, Germany, Belgium, Russian Federation, Israel, Turkey, Finland, Czech Republic, Germany, Italy, Sweden and the USA. Materials and Methods Meetings of the Sheffield Group are held annually, hosted by one of the national labs. The purpose is to keep directors informed about programmes of research and national policy issues, and occasional collaborations across Institutes are also agreed. In 2003, PEROSH emerged from the Sheffield Group as a more formal mechanism to support joint research activities in Europe. Results The most recent meeting in Korea showcased the value of this network and provided insights which would not have been delivered through any other network. Conclusions The Sheffield Group is the only global network which supports directors of national occupational health and safety facilities. This not only allows a unique agenda of topics to be discussed but also helps to define why such national facilities are needed and the added value that they bring to national health and safety systems.
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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 | 0.028 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.010 | 0.004 |
| Insufficient payload (model declined to judge) | 0.174 | 0.031 |
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".