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Record W2067269499 · doi:10.1108/jices-01-2014-0004

Young people online and the social value of privacy

2014· article· en· W2067269499 on OpenAlexaffabout
Valerie Steeves, Priscilla M. Regan

Bibliographic record

VenueJournal of Information Communication and Ethics in Society · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsInternet privacyValue (mathematics)Information privacyContext (archaeology)NegotiationPublic relationsSociologyPolitical scienceComputer scienceSocial science

Abstract

fetched live from OpenAlex

Purpose – The purpose of this paper is to develop a conceptual framework to contextualize young people’s lived experiences of privacy and invasion online. Social negotiations in the construction of privacy boundaries are theorized to be dependent on individual preferences, abilities and context-dependent social meanings. Design/methodology/approach – Empirical findings of three related Ottawa-based studies dealing with young people’s online privacy are used to examine the benefits of online publicity, what online privacy means to young people and the social importance of privacy. Earlier philosophical discussions of privacy and identity, as well as current scholarship, are drawn on to suggest that privacy is an inherently social practice that enables social actors to navigate the boundary between self/other and between being closed/open to social interaction. Findings – Four understandings of privacy’s value are developed in concordance with recent privacy literature and our own empirical data: privacy as contextual, relational, performative and dialectical. Social implications – A more holistic approach is necessary to understand young people’s privacy negotiations. Adopting such an approach can help re-establish an ability to address the ways in which privacy boundaries are negotiated and to challenge surveillance schemes and their social consequences. Originality/value – Findings imply that privacy policy should focus on creating conditions that support negotiations that are transparent and equitable. Additionally, policy-makers must begin to critically evaluate the ways in which surveillance interferes with the developmental need of young people to build relationships of trust with each other and also with adults.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score0.403

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.047
GPT teacher head0.388
Teacher spread0.341 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations49
Published2014
Admission routes2
Has abstractyes

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