From early trauma to later leadership: Parents’ workplace safety incidents and children’s later leader emergence
Bibliographic record
Abstract
Work injuries are not uncommon; their effects go well beyond injured workers, with their children at risk of experiencing negative mental health outcomes. We develop a conceptual model in which children's perceptions of parents' work injury severity are indirectly associated with leader emergence in young adulthood through their experience of context-specific psychological distress and posttraumatic growth, with parenting (i.e., authoritative parenting) and family (i.e., household chaos) factors moderating the relationship between psychological distress and posttraumatic growth. We conduct two studies, each using time-separated, online surveys. Participants in Study 1 ( N = 143) and Study 2; ( N = 325) are young adults from the United States, United Kingdom and Canada (Study 1), and Canada (Study 2) who had a parent involved in a workplace safety incident when they were between the ages of 3–17 years. Support emerged for the indirect effects of perceived severity of parents' work injury on leader identity (Study 1), and leader role occupancy (Study 2) through psychological distress and posttraumatic growth. Authoritative parenting and household chaos moderated the effects of psychological distress on posttraumatic growth in Study 2. By highlighting the effects of non-normative, potentially traumatic events in childhood on later leader emergence, these results (1) demonstrate the need to extend the lifespan development model of leader emergence, and consider the consequences of workplace safety incidents beyond (2) injured workers themselves, and (3) only negative outcomes.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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 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".