A moderated-mediated model of youth safety
Bibliographic record
Abstract
Purpose Workplace injury and death of young persons are important concerns. The purpose of this paper is to focus on the mediating role of safety behaviours underpinning the relationship between perceived safety climate (PSC) and injuries, and the moderating roles of safety-specific transformational leadership (SSTL), general transformational leadership (GTL) and training in influencing the mediation, for young workers. Design/methodology/approach An exploratory, online questionnaire was completed by 367 university students employed in various industries. Data were analysed using moderated mediation. Findings Safety behaviours mediated the relationship between PSC and injuries. SSTL moderated the relationship between PSC and safety behaviours, but GTL did not. Training did not positively moderate the relationship between safety behaviour and injuries, yet may still inform us on the training by referent others since safety behaviour mediated the relationship between PSC and injuries when SSTL, GTL and training were high. Research limitations/implications A student sample was utilised, but was appropriate in this context as it is representative of the type of workers being studied. Longitudinal data with larger diverse data sets should be incorporated. Practical implications Business owners must utilise both forms of leadership to promote a safe workplace. HR and H&S professionals must continue to encourage this promotion. Social implications Safety training and leadership are important for policy makers and regulators to reduce workplace injuries for youth workers. Originality/value This study is the first to test youth H&S using moderated mediation. Safety specific and general forms of leadership and training are important predictors.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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; both teacher heads agree on what is shown here.
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".