Verification of a Predictive Model of Psychological Health at Work in Canada and France
Bibliographic record
Abstract
The purpose of this study was to test the invariance of a predictive model of psychological health at work (PHW) in Canada and France. The model a) defines PHW as an integrative second-order variable (low distress, high well-being) and b) includes three categories of PHW inductors (job demands, personal resources and social-organizational resources) and one psychological intermediate variable (needs satisfaction) that were found to be directly or indirectly related to PHW in a previous study on a sample of French teachers (Boudrias, Desrumaux, Gaudreau, Nelson, Savoie and Brunet, 2011). To test if this model is invariant across countries, these data from French teachers (N = 391) were reanalyzed and compared with data from a sample of Canadian teachers (N = 480) who completed the same set of questionnaires. Results from structural equation modeling analyses indicated that the model is completely invariant across the two samples. Therefore, pathways to PHW appeared to generalize across these samples of teachers without the addition of other cultural variables. This PHW model suggests that personal resources exert considerable influence directly and indirectly on psychological health through multiple mediators. Research implications and study limitations are discussed.
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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 | 0.001 | 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 | 0.000 | 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) | 0.000 | 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".