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Record W2811507926 · doi:10.1186/s12995-018-0202-0

“Areas of Worklife scale” (AWS) short version (Spanish): a confirmatory factor analysis based on a secondary school teacher sample

2018· article· en· W2811507926 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Occupational Medicine and Toxicology · 2018
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsAcadia University
Fundersnot available
KeywordsMedicineConfirmatory factor analysisScale (ratio)Sample (material)Public healthStructural equation modelingNursingStatisticsCartography

Abstract

fetched live from OpenAlex

This study examines the construct validity of the Areas of Worklife Short Scale, a practical instrument to measure employees’ perceptions of their work environments in the sample of secondary obligatory education teachers in Spain. Conducted in 33 centers of secondary obligatory education in Spain (N = 677). Confirmatory Factor analysis for 3 different models for the 29-items version and 1 model for the 18-items version was tested. Results confirmed that the short AWS short version had the best fit to the data than any other model proposed (GFI-Satorra-Bentler scaled chi-squared = 320.19, × 2/df = 2.337) and good fit indices (CFI = 0.911; RMSEA = 0.046). This analysis ultimately supports the appropriateness of AWS short version to explore areas of worklife and therefore can indicate the factors that contribute to burnout in the sample of secondary obligatory education teachers in Spain. Therefore it has been confirmed that this tool is able to assess the 6 domains of work environment of secondary schools teachers.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.000

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.

Opus teacher head0.055
GPT teacher head0.429
Teacher spread0.374 · 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