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Record W2972232630 · doi:10.60082/2817-5069.3389

Internet Intermediary Liability in Defamation

2019· article· en· W2972232630 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueOsgoode Hall law journal · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicFreedom of Expression and Defamation
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsNoticeIntermediaryLiabilityThe InternetBusinessComplaintLawProfit (economics)Law and economicsInternet privacyPolitical scienceEconomicsComputer scienceMarketingWorld Wide Web

Abstract

fetched live from OpenAlex

Given the broad meaning of publication in defamation law, internet intermediaries such as internet service providers, search engines, and social media companies may be liable for defamatory content posted by third parties. This article argues that current law is not suitable to dealing with issues of internet defamation and intermediary responsibility because it is needlessly complex, confusing, and may impose liability without blameworthiness. Instead, the article proposes that publication be redefined to require a deliberate act of communicating specific words. This would better reflect blameworthiness and few intermediaries would be liable in defamation under this test. That said, intermediaries profit from content, and they have the capacity and flexibility to respond to defamation in a way that courts cannot. The paper therefore also proposes a regulatory framework called notice-and-notice-plus. This would require intermediaries to forward a notice of complaint to content creators, and only to remove content in limited circumstances.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.806
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.020
GPT teacher head0.286
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it