Understanding the relationship between teacher leadership and teacher well-being: the mediating roles of trust in leaders and teacher efficacy
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
Purpose Teacher well-being has been a concern, but there has been a lack of research on how teacher leadership can contribute to teacher well-being in a high-accountability context and a hierarchical education system such as that of China, particularly through the meditating roles of trust in the leader and teacher efficacy. Therefore, the purpose of this study was to understand the relationship between teacher leadership and teacher well-being while exploring the mediating roles of trust in leaders and teacher efficacy in this relationship. Design/methodology/approach Using structural equation modeling (SEM) and bootstrap methods with valid answers from 1,144 teachers in 25 primary schools in 1 Chinese city, this study mainly answered three questions: Is there a significant relationship between teacher leadership and teacher well-being? Is there a significant mediating effect of trust in leaders on the relationship between teacher leadership and teacher well-being? Is there a significant mediating effect of teacher efficacy on the relationship between teacher leadership and teacher well-being? Findings This study reported a positive relationship between teacher leadership and teacher well-being. This study also found positive mediating roles for trust in leaders and teacher efficacy in the relationship between teacher leadership and teacher well-being in a high-accountability and hierarchical system like that of China. Originality/value This study provides an understanding of the transferability of teacher leadership theories across cultures and has practical significance for educational practice in high-accountability and hierarchical education contexts similar to that of China.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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