The Medium is not the Message: Reconciling Reputation and Free Expression in Cases of Internet Defamation
Bibliographic record
Abstract
In this paper the author critiques the approach to defamation over the Internet taken to date by the Canadian common law courts. In the emerging jurisprudence, the courts have relied upon untenably broad generalizations about Internet technology, repeatedly equating it with traditional broadcast media and expressing grave concerns about the corresponding threat to reputation posed by online defamation. This has led the courts to hold that when defamatory words are transmitted using the Internet, this will vitiate the availability of any qualified privilege that would otherwise have immunized the defendant from liability under traditional defamation principles, and substantially increase any resulting award of damages. The author argues that this approach results in a failure to strike the appropriate balance between free expression and the protection of reputation. The jurisprudence can also be seen as a product of a long-standing and unfortunate analytical tendency in defamation law—primarily apparent through the libel/slander distinction—whereby common law courts attach extremely divergent legal consequences to impugned statements based on indefensibly broad generalizations about the degree of danger to personal reputation posed by the medium in which the statement was communicated. Drawing inspiration from a comparison to defamation under the civil law of Quebec, the author proposes a new approach that eschews reliance upon unhelpful analogies and generalizations about particular media including the Internet, and involves the examination of impugned statements on a case-by-case basis, paying careful attention to the context in which these were actually made.
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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 | 0.029 | 0.078 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.014 | 0.048 |
| Scholarly communication | 0.017 | 0.019 |
| Open science | 0.005 | 0.015 |
| Research integrity | 0.023 | 0.014 |
| Insufficient payload (model declined to judge) | 0.003 | 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".