Financial Well-Being among Public Employees in Malaysia: A Preliminary Study
Bibliographic record
Abstract
Public employee’s innovativeness, responsiveness, efficiency and friendliness in services are the core prescriptions to enhance the competitiveness of one’s country. Financial well-being and employees are two aspects that consequently related with each other that have received substantial deliberation from researchers, employers and financial advisor. Financial well-being can affect both direct and indirectly towards an individual, team and also organization. Changes in employee’s financial well-being level whether it becomes high or low will affect their job performance. The purpose of this study is to discuss the level of public employee’s financial well-being in Malaysia as well as to examine the determinants of financial well-being. A total of 73 questionnaires have been distributed through e-survey (email based) using convenient sampling technique in order to conduct this pilot test (pre-test). Only 30 public employees have participated in this study. The results identified that majority of public employees is at the moderate level of financial well-being. Even so, appropriate action should be taken through financial education in order to prevent worst case scenario 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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".