The Study on Factors Influencing Incomes of Laborers in Viet Nam: The Case at Industrial Parks, Economic Zones in Travinh Province
Bibliographic record
Abstract
This study aims to solve the problem of raising incomes, improving the quality of life of Vietnamese workers in industrial parks and economic zones today, specifically in Tra Vinh province, Viet Nam. By the method of primary data collection of 300 employees working in enterprises in Long Duc Industrial Park located in Tra Vinh City; Co Chien Industrial Park located in Cang Long district and Dinh An economic zones located in Tra Cu district; using multivariate regression model; The study showed that there are 6 factors affecting the income of workers: the occupation of workers, working experience, the qualifications of workers, ethnicity, Religion and working environment. In particular, working experience, the qualifications of workers greatly affect the income of employees. From the research results, the author have proposed solutions to improve the income of workers, ensure social security and stabilize the lives of workers in the future.
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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".