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Record W3205431123 · doi:10.1002/pra2.574

Digital Contact Tracing in the <scp>EU</scp>: Data Subject Rights and Conflicting Privacy Governance

2021· article· en· W3205431123 on OpenAlexaff
A Rosenberger, Yan Shvartzshnaider, Madelyn Rose Sanfilippo

Bibliographic record

VenueProceedings of the Association for Information Science and Technology · 2021
Typearticle
Languageen
FieldComputer Science
TopicCOVID-19 Digital Contact Tracing
Canadian institutionsYork University
Fundersnot available
KeywordsContact tracingTracingInternet privacyCorporate governancePolitical scienceData Protection Act 1998Privacy policyInformation privacyComputer scienceComputer securityBusinessLawCoronavirus disease 2019 (COVID-19)

Abstract

fetched live from OpenAlex

Abstract The wide‐spread use of digital exposure notification systems, often called contact tracing apps, raises questions about privacy and efficacy of technosolutionism to address COVID‐19. As part of a broad study of global contact tracing apps, this poster explores the governance and privacy implications of European digital contact tracing solutions. We explore legal justifications for data collection in these apps and data subjects' rights with respect to the General Data Protection Regulation (GDPR) and national laws throughout Europe.

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 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)0.002
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.719
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0010.013
Open science0.0020.001
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 head0.017
GPT teacher head0.265
Teacher spread0.248 · 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 teacher head, not a consensus.

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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Association for Information Science and TechnologySame topicCOVID-19 Digital Contact TracingFrench-language works237,207