Cybertorts in Canada: Trends and Themes in Cyber-Libel and Other Online Torts
Bibliographic record
Abstract
The article identifies trends and themes in cybertorts in Canada, examining especially how Canadian courts are approaching online defamation and internet jurisdiction issues. In cyberlibel cases, as communication technologies of online chat groups, websites and email are assimilated, some courts are re-considering traditional notions about communications, especially those that associate a message's influence with an author's identity, and concluding that internet communications may be believed more readily than communications in print; anonymous messages may be believed more readily than those by identified speakers; and communications in non-print media, with their correspondingly technologically enhanced features of hyperlinking, cross-referencing, archiving and searching, may be more powerful and memorable. Some of these views, however, are at odds with traditional assumptions about credibility, which historically has been correlated with the speaker's identifiability, bias, experience, and authority. The paper in particular questions the emerging view in internet defamation cases in Canada that anonymous online speech may be more likely to be believed than the same words published in print. While it is important to pay attention to the internet's particular features, including speed and interactivity, traditional theories about how credibility is evaluated and what criteria are weighed to assess belief should still be considered in this medium. Technology may widely expand who can be heard, but it does not necessarily follow that it should, or does, widely expand what and who is believed. The paper also considers internet jurisdiction theory in Canada and argues that Canadian courts should apply general internet principles under Canadian law rather than turning to internet-specific jurisdiction tests developed in other countries.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.018 | 0.033 |
| Science and technology studies | 0.015 | 0.011 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".