An assessment of the overlap between morale and work engagement in a nonoperational military sample.
Bibliographic record
Abstract
The degree of overlap between two positive motivational constructs-morale and work engagement-was assessed in a random sample of Canadian Armed Forces personnel stationed across Canada (N = 1,224). Based on self-determination theory and past research, job-specific self-efficacy, trust in teammates, and job significance were expected to be associated with morale and work engagement. Structural equation modeling analyses revealed that morale and work engagement were highly positively correlated, but had different patterns of association with predictor and outcome variables. Although trust in teammates and job significance predicted both morale and work engagement, job-specific self-efficacy predicted morale but not work engagement. Willingness to deploy on operations, turnover intentions, and psychological distress were predicted by both morale and work engagement, but morale was a better predictor of psychological distress and work engagement was a stronger predictor of turnover intentions. Together, the results suggest that, despite their overlap, morale and work engagement, as defined and measured herein, are not interchangeable.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".