The effect of emotional dissonance and emotional intelligence on work–family interference.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this study, we examined the relationship between emotional dissonance and work-to-family inference (WFI) and whether emotional intelligence moderated the association between emotional dissonance and WFI. Data were collected at two time points. At Time 1 (T1), we measured emotional dissonance, demographic variables (i.e., gender, age, marital status, number of children), negative affectivity, emotional intelligence, and WFI (T1). At Time 2 (T2), WFI was measured again. A total of 155 valid questionnaires were collected at two time points. Hierarchical regression analyses showed that emotional dissonance at T1 was a salient predictor of WFI at Time 2, even when WFI at Time 1 and other variables were controlled. One subdimension of emotional intelligence-namely regulation of emotion-was also significantly related to WFI at T2. However, emotional intelligence did not moderate the association between emotional dissonance and WFI.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 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 it