Student Edition of the Income Tax Act 2009: Featuring 'How to Manage a Difficult Tax Partner' (A Tax Novella)
Bibliographic record
Abstract
The Student Edition of the Income Tax Act is designed to supplement tax courses taught at law and business schools. It can also serve as a convenient reference tool for lawyers, accountants, and others who work in the tax field. The book is comprised of two elements: selected provisions of the federal Income Tax Act and a tax teaching tool called ‘How to Manage a Difficult Tax Partner.’ The second element - the ‘tax novella’ - is meant to focus a tax student’s attention on the most critical ingredients that combine to form the complex stew of tax law. The text incorporates seven core tax principles, one in each chapter, that animate the tax rules throughout the Act. The tax novella is also designed to amuse and entertain readers and draw them into learning tax law: readers are asked to try to answer problems at the end of each chapter to ensure the survival of the story's protagonist, Jason Lumberlane.The attached excerpt provides the first three chapters of How to Manage a Difficult Tax Partner.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.033 | 0.009 |
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".