Workplace safety climate assessment based on behaviors and measurable indicators
Bibliographic record
Abstract
Abstract Previous conceptualizations of safety climate present snapshots of the state of workplace safety. In reality, the factors of workplace safety climate are complex and need to be analyzed using a systemic approach. In this article, we expand on the customary concept of safety climate, and propose a systemic research framework that integrates four study fields: engineering, ergonomics, operation management, and technology management. In this framework, we define micro and macro safety climate concepts based on the study object and organizational hierarchy. Our model focuses on two safety climate dimensions: behaviors and measurable indicators. First, we propose that the safety process consists of four basic behaviors: perceive, decide, communicate, and act (PDCA). These PDCA behaviors constitute a safety climate sociotechnical system involving the three roles of operator, supervisor, and manager. We then present 12 measurable indicators of PDCA behaviors for each safety climate research field to advance the systematic assessment of both qualitative and quantitative facets of safety climate. © 2008 American Institute of Chemical Engineers Process Saf Prog, 2008
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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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".