Unrealistic Optimism, Fatalism, and Risk-Taking in New Zealand Farmers’ Descriptions of Quad-Bike Incidents: A Directed Qualitative Content Analysis
Why this work is in the frame
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Bibliographic record
Abstract
Quad-bike incidents are a major cause of occupational injury and fatality on farms warranting health and safety attention. As part of a larger study, we carried out a face-to-face survey with 216 farmers in New Zealand. We quantitatively identified farmers' propensity for risk-taking, unrealistic optimism, and fatalism as risk factors in quad-bike loss-of-control events (LCEs). The purpose of the analysis presented in this article was to use these same farmers' recollections of LCEs to explore the a priori constructs in more detail using qualitative methods. Participants reporting one or more LCEs described their first LCE and any experienced in the previous 12 months. Participants provided open-text responses about what occurred at each LCE, their reflections, and general thoughts on LCE risk factors. Directed qualitative content analysis (QCA) was used to "unpack" risk-taking, unrealistic optimism, and fatalism whilst also delineating any additional concepts that farmers associate with LCEs. Risk-taking elements were more evident than unrealistic optimism or fatalism and more suggestive of farmers finding themselves in risky situations rather than engaging in risk-seeking behavior per se. Additional inductively derived categories of fatigue/stress, multitasking, inexperience, and quad-bike faults highlight the complex nature of LCEs and the importance of risk assessment covering these concepts as well as risky situations.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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