The Tax Court's Informal Procedure and Self-Represented Litigants: Problems and Solutions
Bibliographic record
Abstract
The informal procedure of the Tax Court of Canada is generally recognized as providing easier, speedier, and less expensive access than the general procedure. However, problems persist in the case of self-represented litigants, who accounted for 44 percent of all Tax Court cases decided in January 2005. Owing to their lack of knowledge of the judicial process, many of these taxpayers may not be receiving a fair outcome in spite of attempts by judges to make the process as balanced as possible. This article draws on numerous Tax Court transcripts to illustrate the issues involved, particularly in connection with rules of procedure and rules of evidence. The author arrives at three main recommendations. First, the four key concepts of onus, relevancy, credibility, and corroboration should be briefly explained to all self-represented taxpayers before the start of the hearing. Second, greater judicial intervention in the proceedings is necessary in the case of self-represented taxpayers in order to reduce delays, permit the presentation of all the relevant evidence, and generally allow for a fair trial. Third, to emphasize the four key concepts noted above, and to explain the role and procedures of the Tax Court, an order or direction on these topics should be issued by the chief justice of the court and sent to all litigants who are not represented by a lawyer. Other ideas include full disclosure and pretrial conferences for cases with self-represented litigants.
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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 | 0.041 | 0.133 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.016 | 0.033 |
| Scholarly communication | 0.017 | 0.011 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".