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Record W2999934405 · doi:10.1017/aju.2019.79

A Tale of Two Privacy Laws: The GDPR and the International Right to Privacy

2020· article· en· W2999934405 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.

Bibliographic record

VenueAJIL Unbound · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean Criminal Justice and Data Protection
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsInternational Covenant on Civil and Political RightsGeneral Data Protection RegulationInformation privacyThe Right to PrivacyPolitical sciencePrivacy lawRight to be forgottenInformation privacy lawData Protection Act 1998Right to privacyEuropean unionPrivacy policyPrivacy laws of the United StatesLawInternet privacyData Protection DirectiveBusinessFundamental rightsHuman rightsEuropean Union lawInternational tradeComputer scienceRight to property

Abstract

fetched live from OpenAlex

The European Union's General Data Protection Regulation (GDPR) is widely viewed as setting a new global standard for the protection of data privacy that is worthy of emulation, even though the relationship between the GDPR and existing international legal protections for the right to privacy remain unexplored. Correspondingly, this essay examines the relationship between these two bodies of law, and finds that the GDPR's provisions are neither necessary nor sufficient to protect the right to privacy as enshrined in Article 17 of the International Covenant on Civil and Political Rights (ICCPR). It argues that there are other equally valid and effective approaches that states can pursue to protect the right to privacy in an increasingly digital world, including the much-maligned American approach of regulating data privacy on a sectoral basis.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.956
Threshold uncertainty score0.285

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.046
GPT teacher head0.323
Teacher spread0.278 · 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