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Record W2247786537

Should the Whole World Be Watching? The Tension between Social Networks and National Privacy Policies

2010· article· en· W2247786537 on OpenAlexaboutno aff
Phyllis Bernt

Bibliographic record

VenueSSRN Electronic Journal · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsnot available
Fundersnot available
KeywordsInternet privacyInformation privacyPrivacy by DesignPrivacy policySocial network (sociolinguistics)PremisePersonally identifiable informationBusinessPublic relationsSocial mediaComputer securityPolitical scienceComputer scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

It is a truism that social networks are changing the way people communicate and share information. Social network members share a wealth of information about themselves -- and others -- with friends and strangers all over the world. Social network providers and social network members are, however, operating in uncharted territory when it comes to privacy. Their responsibilities are by no means clear. The underlying premise of social networks is that an immense amount of personal information should be widely and easily accessible; this puts social network providers on a collision course with privacy regulators and policy makers who emphasize limitations on the uses of personal information and the importance of only using information with proper consent. While privacy rules present a challenge to the viability of social network providers’ business plans, the social networks themselves are a test of the effectiveness of privacy regulation for this new social medium. The outcome of this clash between access and privacy, and its impact on social networks, is not certain. The extent of this clash, and the uncertainty of its outcome, is nowhere more evident than in Facebook’s continued privacy battles.Using Facebook as a focus of analysis, this paper explores the tension between the social network business model and the provisions of privacy regulations. As the provider of the world’s largest social network, Facebook is an excellent example of a network provider whose aggressive business plan has led to numerous complaints and investigations by privacy regulators. An examination of the privacy complaints filed against Facebook in the U.S., Canada, and the U.K., as well as an evaluation of EU recommendations for tighter privacy oversight of social networks, provides an opportunity to both identify the privacy issues involved in social networking and compare the differing privacy regimes followed in Europe, Canada, and the U.S. At the same time, this analysis offers some insights regarding the potential impact of privacy regulation on the operations of social network providers, as well as the feasibility of implementing a robust privacy regimen in the social networking environment

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.394
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.004
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 head0.033
GPT teacher head0.323
Teacher spread0.290 · 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
Published2010
Admission routes1
Has abstractyes

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