Effects of Fringe Benefits on Employee Loyalty: A Study on University Teachers in Khulna City of Bangladesh
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
The aim of this study was to examine the effects of fringe benefits on employee loyalty in the context of university teachers. The study sample consisted of 100 university teachers who were randomly selected from both private and public universities situated in Khulna city of Bangladesh. Data were collected through a self-administered questionnaire survey. To test the study hypotheses, data were analyzed employing correlation and multiple regression analysis tools. Results of correlation analysis reveal that fringe benefits (insurance & retirement benefits, payments for time not worked, education & development opportunities, flexible working hours, and employee welfare benefits) are positively related to employee loyalty. Regression statistics shows that 25.6% variance of employee loyalty can be explained by the fringe benefits. The study findings also indicate that flexible working hours (β = 0.296, Sig. = 0.001) has the most significant contribution in explaining employee loyalty among the university faculty members employed in Khulna city of Bangladesh.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.000 | 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