The Influence of Value Added Tax (Vat) Assessment on Income Distribution of Consumer of Garment in West Java
Bibliographic record
Abstract
Act No. 18 of 2000 regarding burden of Value Added Tax is bore by the consumer, but the implementation indicates that there is industrial policy to bear a part or an overall of VAT. Accordingly, if burden distribution is progressive, the higher household income means a higher VAT burden bore by the consumer, conversely, the lower consumer income, the lower VAT bore by him. Consequently, it will cut real income down, and it affects consumer’s purchasing power. Research objectives are to find out if distribution of industrial VAT burden is progressive, regressive or proportional, and to find out to what extend influence of VAT on distribution of household income. The influence of VAT on distribution of consumer’s household income will be tested by applying effective tariff, Gini index, and progressivity index. The findings indicate that effective tariff of VAT is progressive (positive value) meaning that consumer and industrial VAT burden is increasing. Calculation of Gini index before and after VAT assessment make consumer’s earning gaps smaller, while calculation of progressivity index indicates industrial tax system is progressive (positive value) indicating that most of consumers come from middle to upper class.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".