Religiosity as a moderating variable on the effect of love of money, Machiavellian and equity sensitivity on the perception of tax evasion
Bibliographic record
Abstract
This study aims to obtain an empirical evidence on how religiosity is moderating the effect of love of money, Machiavellian, and equity sensitivity on the perception of tax evasion. The populations in this study are individual taxpayers registered in all Pratama tax offices in Bali. Sampling was determined using the probability sampling method with proportional stratified random sampling technique. This study uses 400 research samples. The data analysis technique used is multiple linear regression analysis and moderated regression analysis. The test results provide empirical evidence that love of money and Machiavellian have a positive effect on the perception of tax evasion, however, equity sensitivity has no effect on the perception of tax evasion. The results of subsequent tests provide empirical evidence that intrinsic religiosity and extrinsic religiosity can moderate the effects of love of money, Machiavellian, and equity sensitivity on perceptions of tax evasion.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".