Teachers’ wellbeing at work: a Finnish survey study on teachers’ work experiences
Bibliographic record
Abstract
This study explores the working life experiences of teachers, adopting a salutogenic perspective emphasising positive health, wellbeing and health promotion principles. An electronic survey was sent out to members of a trade union for teachers in spring 2020. More than 1,300 teachers responded to the survey, including the Work Experience Measurement Scale (WEMS) instrument, which contains six dimensions of work experience: supportive work conditions, internal work experiences, autonomy, time experience, leadership and process of change. Correlation and regression analyses were conducted to examine the relationships between the variables Age, Workplace, Gender and the six dimensions of WEMS, plus the WEMS total. About half of the teachers reported good or excellent work experience; whereas, nearly a quarter reported poor work experience male teachers rated their time experience higher than their female colleagues; whereas, female teachers’ internal work experiences were better in comparison with their male counterparts. Teachers working at comprehensive school grades 7–9 had significantly lower ratings in the WEMS total than teachers in other workplace groups. Older age predicted lower ratings in the aspect of Process of Change. Teachers, altogether, evaluate their work experiences as reasonably good. Time experience is the most challenging dimension in teachers’ working life.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".