The Difference Between Taxation and Administrative Fees From the Perspective of Administrative Law
Bibliographic record
Abstract
What is tax? What is administrative fee? It is the first question to be proposed in the study on administrative fee. Connotations and denotations of administrative fee could be only determined based on the comparison of administrative fee and tax. The prime difference between tax and fee could be seen from the following three points. First of all, the purpose of collection is different. The purpose or attached purpose for the government to collect tax is to increase fiscal revenues, and offer general and ordinary government services to the public. While the purpose to collect fee is to make up the cost spent in specific services for sake of individuals. Secondly, tax refers to public debts without reciprocal payment, while fee refers to reciprocal payment of specific public services. Thirdly, tax compliant with “capability payment principle” determines tax rate according to “taxation on capability principle” in measuring taxation liability. While by contrast, fee compliant with “user payment principle” or “beneficiary payment principle” determines rate according to “cost or fee compensation principle” or “fee coverage principle” in measuring payment liability.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.018 |
| Scholarly communication | 0.009 | 0.014 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".