Spurring teacher well‐being from teacher leadership and basic psychological needs perspectives
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.
Bibliographic record
Abstract
Abstract This study aims to investigate the linear and nonlinear (non‐compensation) effects of teacher leadership on teacher well‐being dimensions through the three basic psychological needs dimensions (autonomy, competence, and relatedness). This quantitative cross‐sectional study used partial least squares structural equation modelling and artificial neural network (ANN) for data analysis. Data were collected using survey questionnaires from 728 Malaysian primary school teachers. All the direct (linear) and indirect effects of teacher leadership on teacher well‐being dimensions through teachers' basic psychological needs were significant. The ANN analysis revealed that competence, a dimension of teacher basic psychological needs, was the strongest predictor of workload well‐being and student interaction well‐being. Autonomy was the strongest predictor of organisational well‐being. Implications and future studies are presented.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it