Ecosystem functioning across vegetation - production boundaries in brigalow (Acacia Harpophylla) in Southern Queensland
Bibliographic record
Abstract
The mediating effect of job characteristics in the socioeconomic status (SES)-health relationship has not been well studied in the young adult population. The early health trajectory is important to study since the health trajectories of young people shape their health in later years. The purpose of this study was to determine whether the education defined SES-health relationship is mediated through job characteristics, controlling for healthy lifestyle factors in young adults. We hypothesize that accounting for differences in job quality would reduce the education-health gradient. Using a sample of 10,215 Canadian workers aged 20-29 years, we used multivariable logistic regressions to examine the associations of sociodemographic, work, and lifestyle factors with two health outcomes, self-perceived health and work-related injury. The key findings indicate that job characteristics partly explain the education gradient observed in work-related injuries, and to a lesser extent in self-perceived health for working young adults. Our results show that increased physical exertion and working in sales and service or manual occupations were job characteristics which were independently associated with work-related injuries, while low work-related social support and irregular shift work were associated with poor self-perceived health. Lifestyle factors have a greater association with the education-self-perceived health relationship. This pattern of findings suggests that work factors related to education have a more specific effect on occupational health early in the health trajectory. These findings have potential practical implications since policies to reduce poor health must be targeted at appropriate age groups, as workers need to be healthy in their younger years in order to stay in the workforce as they age.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 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".