The Relationship between Job Motivation, Compensation Satisfaction and Job Satisfaction in Employees of Tax Administration – A Case Study in Tehran
Bibliographic record
Abstract
<p>The purpose of this paper is to assess the relationship between job motivation, compensation satisfaction and employees’ job satisfaction in tax organization. In this study, survey research method has been used to collect required data. For the purpose of this case study, a 210 people sample has been selected from research population using simple random sampling method. In order to measure employees’ job satisfaction, Susan J Linz (2002) questionnaire and in order to measure compensation satisfaction Ogenyi Ejye Omar’s model (2006) has been used. This model includes four factors; Payment Justice, Organizational designed procedures, supervisor and performance-based pay. Also Herzberg and Kitchener model has been used to measure employees’ motivation. Data analysis with Pearson correlation coefficient shows a positive relation between job motivation and compensation satisfaction. Qualitative approach implies that organizational justice in payments in important and employees who feel financially discriminated, their job satisfaction is lower compared to other employees.</p>
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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 | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".