The effect of tax morale on tax evasion in the perspective of Tri Hita Karana and tax framing
Bibliographic record
Abstract
This study aims to analyze the effect of tax morale in the Tri Hita Karana perspective and tax framing on tax evasion. The experimental design is a 2×2 between-subject which are 56 taxpayers of the Balinese people who live in Palu City, Indonesia. The tax framing variable is manipulated with positive and negative framing scenarios. Each taxpayer determines the amount of income is reported. If the taxpayer reports that his income is getting closer to the real thing, then it is stated that he is doing a lower tax evasion and vice versa. The test results indicate that in the perspective of Tri Hita Karana, taxpayers with high tax morale undertake lower tax evasion than taxpayers with low tax morale. This study also found that taxpayers with positive framing treatment performed lower tax evasion than taxpayers with adverse framing treatment. The results of this study provide evidence that increasing taxpayer compliance and reducing tax evasion can be done with high tax morale internalized in the Tri Hita Karana culture and framing information positively.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".