Factors Related to Firefighters' Food Behaviors at the Fire Station
Bibliographic record
Abstract
OBJECTIVE: Using a cross-sectional correlational study, the purpose was to quantitatively investigate factors associated to firefighters' food behaviors while on duty at the fire station. METHODS: Two hundred and fifty-two (252) firefighters (males, 96%; age, 39 ± 11 years) completed an online questionnaire assessing diet and exploring factors that could be associated to firefighters' food behaviors at the fire station. RESULTS: First regression analysis showed that level of education, years of experience, self-perceived nutrition knowledge, autonomous motivation, and accessibility to unhealthy foods were the best predictors of healthy food score. Second regression analysis revealed that body mass index, autonomous motivation, and meals interrupted by emergency calls were the best predictors of fast-food score. CONCLUSIONS: This study highlights the various factors associated with firefighters' food behaviors at the fire station.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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 teacher head, 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".