Bibliographic record
Abstract
This article examines the tort of injurious falsehood. While the focus is on Canadian law, much of the analysis will reflect the law in other common law jurisdictions. There is uncertainty with regard to several elements of injurious falsehood. The article considers how to resolve confusion over the meaning of some of those elements, and what the scope of the tort should be in light of modern realities, including the importance of freedom of expression, the role of corporations in 21st century society and the existence of other torts addressing false statements of fact. The chapter also describes the results of a small empirical study of injurious falsehood, which shows that while the tort is not pleaded as often as defamation, defamation has not effectively eclipsed the tort of injurious falsehood. Ultimately, this chapter argues that there remains a role for injurious falsehood, but that it is rightly a narrow one. So long as defamation remains as plaintiff-friendly as it currently is, many cases best thought of conceptually as injurious falsehood will be pleaded as defamation. That is the result of a problem with the scope of defamation law, which in my view should not apply to protect corporate reputation, rather than a problem with the law of injurious falsehood. Further discussion of the scope of Canadian defamation law is beyond the scope of this chapter. Rather, it will focus on clarification and minor changes that ought to be made to the law of injurious falsehood to ensure it achieves the goals it is intended to.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| 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 | 0.004 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".