MétaCan
Menu
Back to cohort

Dealing with Data Privacy Protection: An Issue for the 21st Century

2002· article· en· W2107211241 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

VenueInformation Systems Management · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsShared Services Canada
Fundersnot available
KeywordsInternet privacyBusinessGovernment (linguistics)Identification (biology)Agency (philosophy)BiometricsTracking (education)Personally identifiable informationEuropean unionInformation privacyComputer securityComputer science

Abstract

fetched live from OpenAlex

Abstract In many surveys, Americans identify invasion of privacy as a primary concern. Nonetheless, newer electronic technologies, such as biometric monitoring, Web site tracking, vehicle tracking, basket-level purchase tracking, charge card usage recording, personal information database sales, release of government data to private corporations, facial identification, DNA testing and record keeping, smart card usage, telephone records, e-mail monitoring, and the like, intrude themselves into our private lives on an ever-expanding basis. It seems that every company and every governmental agency has an interest in knowing what we do, what we like and dislike, what we read, how long we sustain interest in something, which stores we frequent, and what we ignore. the European Union (EU) and other countries outside the EU are taking an approach to privacy that companies with an international presence must address to maintain compliance with that approach.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.992
Threshold uncertainty score0.959

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 studies0.0010.000
Scholarly communication0.0010.004
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 head0.075
GPT teacher head0.301
Teacher spread0.226 · 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