Factor structure and correlates of the Mandarin version of the Managing the Emotions of Others (MEOS) scale
Bibliographic record
Abstract
The English-language version of the Managing the Emotions of Others (MEOS) scale has been found to have a six-factor structure. This includes two pairs (Enhance, Divert and Worsen, Inauthentic) that respectively describe prosocial and non-prosocial interpersonal emotion management, together with an emotional concealment factor (Conceal) and a factor assessing poor self-rated emotional skills. A Mandarin translation of the MEOS was completed by 277 Chinese student participants. Factor analysis indicated a four-factor structure comprising a merged Enhance/Divert factor, together with Worsen, Inauthentic and Conceal factors. The emergence of a different factor structure compared to Western samples may be related to culture-dependent attitudes to emotional expression. The associations of the MEOS factors with Five-Factor model personality, the Dark Triad and trait emotional intelligence (EI) were examined; these were similar to but generally weaker than those found for the English-language version.
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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 | 0.000 | 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 | 0.001 | 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".