Income Trusts: A "Tax-Efficient" Product or the Product of Tax Inefficiency?
Bibliographic record
Abstract
Au cours des 18 derniers mois, les marches financiers canadiens ont ete temoin d’une explosion du nombre d’appels publics a l’epargne comportant une structure de fonds de titres a revenu fixe. Bien que la structure elle-meme de fonds de titres a revenu fixe ne soit pas nouvelle, son application aux entreprises a l’exterieur des secteurs traditionnels de l’immobilier et du petrole et du gaz est relativement recente. Selon l’auteur, la proliferation recente des fonds de titres a revenu fixe decoulerait en grande partie du fait que ceux-ci sont utilises comme une forme d’arbitrage fiscal. En effet, cette structure permet aux proprietaires d’une societe imposable de conserver de nombreux avantages non fiscaux s’appliquant aux societes tout en evitant certaines consequences fiscales negatives associees a ce mode d’organisation. Generalement, l’utilisation d’une societe comprend un certain degre de double imposition. Bien que les particuliers actionnaires de la societe qui resident au Canada puissent recouvrer une partie de l’impot sur les benefices paye par la societe au moyen du credit d’impot pour dividendes, la partie non recouvree represente un cout reel a l’egard de l’impot. De plus, si la societe verse des dividendes a des entites exonerees d’impot, comme un regime de retraite ou un regime de revenu differe, aucune somme ne peut etre recouvree
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 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".