MétaCan
Menu
Back to cohort
Record W3135035536

The New Antitrust/Data Privacy Law Interface

2021· article· fr· W3135035536 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

VenueSSRN Electronic Journal · 2021
Typearticle
Languagefr
FieldSocial Sciences
TopicIntellectual Property Law
Canadian institutionsDouglas College
Fundersnot available
KeywordsInformation privacyCompetition (biology)Privacy lawDoctrineCompetition lawLawPrivacy by DesignPrivacy policyIntellectual propertyEconomicsLaw and economicsBusinessPolitical scienceMarket economyMonopoly
DOInot available

Abstract

fetched live from OpenAlex

Antitrust theory portrays data privacy as a factor, like quality, that improves with competition. This Essay argues that view is an incomplete account of the new interface between antitrust and data privacy. The more complex reality is that, over the last twenty-five years, data privacy has also become a separate area of legal doctrine. In that capacity, data privacy law may clash at the margins with antitrust—much like intellectual property or consumer protection law did before it. The Essay sheds new light on this tension at the interface of antitrust and data privacy. It provides a descriptive, historical and comparative account of the friction emerging between these areas of law in the digital economy, where data access can both drive competition and reduce privacy. The Essay then lays out a new approach to analyze claims of conflicting data privacy and competition interests, one that emphasizes the accommodation of both areas of law.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.647
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0000.005
Insufficient payload (model declined to judge)0.0020.001

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 head0.043
GPT teacher head0.321
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