Home <i>and</i> away: personal autonomy limitation in the liminal work context of fly-in-fly-out camps and psychological distress
Bibliographic record
Abstract
Fly-in-fly-out (FIFO) camps are liminal work environments in which work and personal life are blended. In such context, an important characteristic is the limitation to one’s freedom to carry out actions that usually occur outside of work contexts (e.g., choosing when to eat dinner), which we refer to as ‘personal autonomy limitation’. The role of personal autonomy limitation for FIFO workers’ mental health has not been systematically investigated at a larger scale. We test whether personal autonomy limitation predicts workers’ psychological distress and their psychological work detachment while they are at their residential home. We also investigate the moderating role of roster ratios (i.e., the ratio of days workers spend on site and at home) on these hypothesized associations. Online survey data from 1547 Australian resources sector FIFO workers showed that higher levels of perceived personal autonomy limitation in FIFO camps predicted greater psychological distress, with this effect partially mediated by lower detachment from work whilst at home. Roster ratio did not moderate the direct or mediated relationships between personal autonomy limitation in FIFO camps and worker psychological distress. The findings identify personal autonomy limitation as a work design characteristic that is relevant to FIFO and other workers’ mental health.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".