An analysis of three distinct approaches to using defamation to protect corporate reputation from Australia, England and Wales, and Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The use of defamation law to protect corporate reputation is controversial. Australia, Canada and England and Wales have been at the centre of this debate, as although their defamation laws share many common characteristics, they adopt distinct approaches to allowing companies to sue in defamation. Consequently, in all three jurisdictions defamation law remains a cause of action that is relied upon by companies to protect their reputations. The primary concern of this paper is the efficacy of these approaches, 1 particularly in light of the reforms made to Australia's defamation laws, adopted in 2020, that further restrict the right of corporations to sue in defamation. Ultimately, it argues that the Australian and English and Welsh approaches disproportionately disadvantage companies, particularly small ones, whereas the Canadian approach overprotects corporate reputation. It concludes by offering an alternative way forward that, although not perfect, provides a better balance between the interests.
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.
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 | 0.000 | 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 | 0.000 | 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 it