Relationship between Turnover Rate and Job Satisfaction of Foreign Language Teachers in Macau
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
<p>Teachers’ satisfaction and turnover rate are directly connected. Using the Model of Retention, Turnover and Attrition by Gardner (2010), this work analyzed about four Japanese language teachers at extension school and educational learning center in Macau. The data concluded the participants felt unsatisfied because of unrelated assignments, limitation of career development, and anxiety and unsteady of employment. The results showed that respondents had negative feelings towards their job responsibilities and employers. Accordingly, teachers usually face long-term stress and burnout because of multiple responsibilities. Therefore, the unsupportive school context could create a negative effect on job satisfaction and retention of teachers. The theoretical model suggests that negative job attributes have a direct relationship with teacher status and job satisfaction.</p><p><strong><br /></strong></p>
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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