Investigation of the employees’ payment system in an educational institution - A case study
Bibliographic record
Abstract
Nowadays, wage and salary system form the most important issues in any society, and its phenomenon takes dimensions with an expansion of a public organization and NGOs.Organizations provide employees satisfaction through different pay programs, which force them to work down more with higher quality.In this paper, we consider a survey of the payment system in an Iranian university as a case study.The population of this study consists of the existing documents, observations, working managers, supervisors and experts.This study is carried out from the desired community based on the data collected for a period of 18 months and the sample size is about 97 people.We use descriptive statistics to analyze the descriptive data.We also use the one-sample Kolmogorove-Smirnov test, t-test and Friedman test for the questions.The results of the existing payment system show that there is no any good condition and the employee's attitude towards this system are negative based on the collected data.Finally, some suggestions are recommended to improve the existing situation.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".