An Empirical Study of the Performance of University Teachers Based on Organizational Commitment, Job Stress, Mental Health and Achievement Motivation/UNE ETUDE EMPIRIQUE DE LA PERFORMANCE DES ENSEIGNANTS UNIVERSITAIRES BASEE SUR L'ENGAGEMENT ORGANISATIONNEL, LE STRESS AU TRAVAIL, LA SANTE MENTALE ET LA MOTIVATION A LA REUSSITE
Bibliographic record
Abstract
This paper defines and analyzes the concept of the performance of university teachers and identifies the four variables of organizational commitment, job stress, mental health and achievement motivation. Thus, this paper puts forward the hypothesis that the four variables-organizational commitment, job stress, mental health, and achievement motivation play a part in teachers’ job performance. Finally the conceptual model of the job performance of teachers is established based on the above four variables. In research based on interviews, a survey was conducted among some teachers in colleges and universities in Xi'an. Through SEM analysis, the results show that the sustained commitment has a negative effect on work performance while emotional commitment has a positive effect on work performance. Work stress has a positive effect on work performance but mental health has a negative effect on work performance, which is not consistent with the hypothesis. Studies also find that emotion commitment is the intermediary variable of the sustained commitment to job performance. Work pressure is the intermediary variable of work pressure affecting job performance whereas there is a positive correlation between achievement motivation and mental health.Keywords: organizational commitment; work pressure; mental health; work /job performance
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| 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 | 0.000 |
| 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".