EFFECTS OF COMPENSATION, CAREER DEVELOPMENT, WORK DISCIPLINE \nAND WORK ENVIRONMENT ON JOB SATISFACTION AMONG PRIVATE \nSCHOOL TEACHERS IN LAHAD DATU, SABAH
Bibliographic record
Abstract
This chapter sets the scene for the study and informs the reader about the issue at hand. It highlights the significance of the study and distils it down to the thesis statement. Following that, the thesis's goals, objectives, and questions are provided. Finally, important definitions \nof terms used throughout the study are supplied in the concluding section. In organisational science and organisational behaviour, job satisfaction is not a new \nphenomenon. It's one of the things that's piqued the curiosity of academics in the field. For over six decades, many studies have been conducted and thousands of articles have been published on this topic (Zembylas & Papanastasiou, 2006). The majority of the studies, however, have been conducted in affluent countries such as the United States of America, the United Kingdom, Canada, and New Zealand, with only a few studies conducted in developing countries. This means that there is more literature on teacher work satisfaction in industrialised countries than in emerging countries, particularly Malaysia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".