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Record W4414244150 · doi:10.1080/2331186x.2025.2560058

Teachers’ wellbeing at work: a Finnish survey study on teachers’ work experiences

2025· article· en· W4414244150 on OpenAlexaboutno aff
Stina Fredrika Lähteenmäki, Lisbeth Fagerström, Anna K. Forsman, Auvo Rauhala

Bibliographic record

VenueCogent Education · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHealth, psychology, and well-being
Canadian institutionsnot available
FundersSvenska Kulturfonden
KeywordsWork (physics)Scale (ratio)Promotion (chess)Work experiencePerspective (graphical)Survey data collectionQuarter (Canadian coin)Well-beingDimension (graph theory)

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.093
GPT teacher head0.476
Teacher spread0.382 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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