Employees’ Satisfaction of Government Organization in Tangail City, Bangladesh
Bibliographic record
Abstract
Employees' satisfaction is directly related to their commitment, citizenship behavior, turnover, absenteeism, dedication and performance. Job satisfaction is important to attract and retain talent workforce. Organization can ensure a competitive advantage over the key rivals through confirming the satisfaction of employees towards job. Organization need to meet the expectations of employees’ which shall ensure their job satisfaction. The purpose of the study is to measure the job satisfaction in government employees of Tangail district. Primary data was used in the study and the sample size of the study was 80. The study revealed the key facets of job satisfaction in government sector of Bangladesh. Factors including salary of employees, performance appraisal system, promotional strategies, employee’s relationship with management and other co- employees, training and development program, work burden, influence of higher authority and working hours are found important for improving job satisfaction of govt. employees in Tangail city. Increase in level of these factors improves overall satisfaction of employees which is identified by using statistical technique.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".