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Record W2768174928 · doi:10.1177/1473779517739798

The need for an intrusion upon seclusion privacy tort within English law

2017· article· en· W2768174928 on OpenAlexaboutno aff
John Hartshorne

Bibliographic record

VenueCommon Law World Review · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsnot available
Fundersnot available
KeywordsTortSeclusionPunitive damagesLawConfidentialityPolitical scienceIntrusionRight to privacyCommon lawPrivacy laws of the United StatesEnglish lawInformation privacyComputer security

Abstract

fetched live from OpenAlex

In the United States, New Zealand and the Canadian province of Ontario, recognition has been afforded to privacy torts remedying intrusions upon seclusion or solitude, and the creation of such a tort has also been recommended by the Australian Law Reform Commission. In England and Wales, recognition has so far only been afforded to a privacy tort remedying misuse of private information. This article considers the current prospects for the recognition of an intrusion upon seclusion tort within English law. It will be suggested that there is less necessity for such recognition following the apparent recent confirmation by the decisions in Gulati v MGN and Vidal-Hall v Google that misuse of private information claims may still be brought where there is no ensuing publication of wrongly acquired private information. Given that intrusions commonly result in the acquisition of private information, it will be suggested that many of the privacy interests protected by the intrusion torts in other jurisdictions may now therefore be protected in English law through a claim for misuse of private information.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.099
Threshold uncertainty score0.196

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.010
Scholarly communication0.0080.009
Open science0.0010.003
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0030.001

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 head0.061
GPT teacher head0.367
Teacher spread0.306 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2017
Admission routes1
Has abstractyes

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