Job Satisfaction of IT Workers in East Asia
Bibliographic record
Abstract
The purpose of this study is to explore the drivers of job satisfaction of IT workers in the East Asian context, particularly in Taiwan, Japan, and China. Using data collected from IT workers, decision tree inductions were employed to identify the predictors of job satisfaction. Results indicate that the level of education has no effect on job satisfaction. Overall, higher uncertainty avoidance results in lower job satisfaction, and more experienced IT workers appear to be more satisfied. In Taiwan, longer serving IT workers, who are likely to hold more senior positions and spend more time on the job, are more satisfied with their jobs. Similarly, in Japan, older IT workers are more satisfied. In China, job satisfaction of IT workers differs across job roles and industries. It is recommended that management practices and policies in Taiwan focus on bridging gaps between longer serving and newer IT workers in terms of their ability to handle ambiguous work situations; whereas in Japan, these should focus on providing work flexibility and stress management programs to allow room for family support. In China, these should be tailored to specific job roles and industries in view of their different experiences with job satisfaction determinants.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".