Bibliographic record
Abstract
The purpose of this study was to examine the mentality of Chinese teachers regarding their use of humour in coping with stress. Specifically, the study investigated their frequency of use of humour in coping with stress as compared to other coping styles and their perceptions about the relationship of humour with other coping styles. Data were collected from a sample of 789 Chinese teachers holding teaching posts at local Hong Kong secondary schools. Based on responses made to the COPE questionnaire, there was evidence that Chinese teachers had a lower frequency of use of humour as compared to other coping styles. As suggested by the results of a factor analysis, there was a perception among Chinese teachers that the use of humour was related more closely to escaping and/or avoidance as coping strategies, but more differentiable from problem-focused/task-oriented and emotional/social coping. It is interesting to find that the results of our study echoed those of a previous crosscultural comparison between Chinese and Canadian university students, in which the Chinese university students reported less use of humour in coping with stress than did their Canadian counterparts. These results have provided some empirical support for the notion that "humor has been traditionally given little respect in Chinese culture mainly due to the Confucian emphasis on keeping proper manners in social interactions" (Yue, 2010, p. 403). As teachers in Chinese societies are regarded as persons who are full of wisdom and capable of problem-solving, it is expected that they should act as role models to their students. These social expectations on Chinese teachers could further mould their perceptions on the use of humour in coping with stress.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".