THE TORT OF CONVERSION AND THE COLLECTING BANK: TEVA CANADA LTD V BANK OF NOVA SCOTIA
Bibliographic record
Abstract
The question of who should bear the loss when an employee defrauds an employer by means of cheques drawn on the employer’s account has arisen frequently in banking law. Yet an answer which accords with the common sense that the employer and/or employee should do so eludes the Supreme Court of Canada, in contrast to that result in other common law jurisdictions. In a recent case, Teva Canada Ltd v Bank of Nova Scotia, the Court declined leave to appeal in a case which would have challenged the Court to reconsider Boma Manufacturing Ltd v CIBC and the vexed issues canvassed there of the meaning of sections 20(5) and 165(3) of the Bills of Exchange Act, and of the common law doctrines of estoppel by negligence, contributory negligence and vicarious liability. This paper sets out these legal issues and a possible resolution in the hope that the court will revisit this frequent fact paradigm in the future
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".