Policy Forum: Some Reflections on Ethical Considerations in Tax Litigation
Bibliographic record
Abstract
Discussion of ethics in taxation usually concerns tax avoidance. But what ethical principles are or should be involved in the conduct of tax litigation? Both parties must observe the ordinary rules of conduct required of them by the court. Are they free, however, to advance any argument to make their case? Taxpayers will be appealing a tax assessment contrary to their view of the tax that the law requires of them. They are bound to make any argument that is open to them. A revenue authority should have broader considerations in mind, as the body responsible for the overall administration of the tax system and as a repeat litigant in court. Consistency of approach and respect for the integrity of the tax system and for a taxpayer's right to demonstrate that tax is not legally due should be among the ethical principles that the revenue authority adopts in conducting tax litigation.
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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 | 0.070 | 0.085 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.039 | 0.064 |
| Scholarly communication | 0.045 | 0.041 |
| Open science | 0.009 | 0.011 |
| Research integrity | 0.156 | 0.072 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".