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Record W1516966560 · doi:10.1080/1369118042000208924

Situating Privacy Online

2004· article· en· W1516966560 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInformation Communication & Society · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsInternet privacyVariety (cybernetics)Neighbourhood (mathematics)The InternetEthnographyMoment (physics)Computer scienceSociologyWorld Wide Web

Abstract

fetched live from OpenAlex

Media and research reports point to the issue of privacy as the key to understanding online behaviour and experience. Yet it is well recognized within privacy-advocacy circles that ‘privacy’ is a loose concept encompassing a variety of meanings. In this article we view privacy as mediating between individuals and their online activities, not standing above them, and as being constantly redefined in actual practice. It is necessary to examine, therefore, what individuals are reacting to when asked about online privacy and how it affects their online experience. This article is based on data generated in the Everyday Internet study, a neighbourhood- based, ethnographic project being conducted in Toronto, Canada, that investigates how people integrate online services in their daily lives. We propose that there are three organizing ‘moments’ of online privacy: the moment of sitting in front of the computer, the moment of interaction with it, and the moment after the data has been released.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.840
Threshold uncertainty score1.000

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 studies0.0020.000
Scholarly communication0.0000.004
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 head0.042
GPT teacher head0.330
Teacher spread0.288 · 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