The one that got away: Lessons learned from the evaluation of a safety training intervention in the Australian prawn fishing industry
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Fishing is an extremely hazardous occupation with one of the highest rates of work-based injuries and fatalities globally. Psychology-based safety training represents one approach to improving fishing safety by addressing safety-related attitudes and beliefs, as well as fostering safety knowledge and more positive safety behaviors (such as safety compliance and safety participation). Partnering with a fishing industry association, we evaluated the impact of safety training within the Australian prawn fishing environment. The study employed a longitudinal design with three data collection points: baseline (pre-program), proximal follow-up (immediately post-program), and one-month follow-up. Although some positive changes were observed for safety knowledge and safety compliance, we encountered logistical challenges that limited our ability to evaluate comprehensively the efficacy of the safety training. Consequently, we provide an analysis of ‘lessons learned’ and offer practical advice to assist applied safety researchers in conducting future safety training studies in the fishing industry. We also describe our psychology-based safety training in detail with the intention of informing future intervention development in this at-risk industry setting.
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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 | 0.049 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it