Comparison of expert-rater methods for assessing psychosocial job strain
Bibliographic record
Abstract
OBJECTIVES: This study tested the reliability and validity of industry- and mill-level expert methods for measuring psychosocial work conditions in British Columbia sawmills using the demand-control model. METHODS: In the industry-level method 4 sawmill job evaluators estimated psychosocial work conditions at a generic sawmill. In the mill-level method panels of experienced sawmill workers estimated psychosocial work conditions at 3 sawmills. Scores for psychosocial work conditions were developed using both expert methods and applied to job titles in a sawmill worker database containing self-reported health status and heart disease. The interrater reliability and the concurrent and predictive validity of the expert rater methods were assessed. RESULTS: The interrater reliability and concurrent reliability were higher for the mill-level method than for the industry-level method. For all the psychosocial variables the reliability for the mill-level method was greater than 0.90. The predictive validity results were inconclusive. CONCLUSIONS: The greater reliability and concurrent validity of the mill-level method indicates that panels of experienced workers should be considered as potential experts in future studies measuring psychosocial work conditions.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".