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Record W2089129701 · doi:10.1177/135485650501100208

Information Privacy and Mobile Phones

2005· article· en· W2089129701 on OpenAlexaboutno aff
Gordon A. Gow

Bibliographic record

VenueConvergence The International Journal of Research into New Media Technologies · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsnot available
Fundersnot available
KeywordsInternet privacyEntitlement (fair division)Mobile phoneBusinessAnonymityInformation privacyPrivacy policyPrivacy by DesignPhoneSoftware deploymentPersonally identifiable informationComputer securityComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

Renewed concerns about information privacy and mobile phones have surfaced with the early deployment of location-based services in North America, and specifically with the Federal Communications Commission (FCC) led public safety initiative known as Wireless E9-1-1. Initial scholarly research in this area has focussed on the use and disclosure of geographic location information of mobile phone subscribers and on the terms and conditions by which this information can be made available for lawful access or commercial purposes. This paper refers to this body of research as the 'first domain' of information privacy research, and describes some of the key findings and contributions for policy research on customer proprietary information and customer consent. The paper then turns to introduce and describe an emerging 'second domain' of information privacy concerned with the popular adoption of anonymous prepaid mobile phone services. The distinguishing characteristic of this second domain of research is its focus on debates about the legitimacy of regulatory requirements to collect and verify customer details at the point of purchase. This paper draws on findings from an empirical study undertaken in Canada to identify some initial parameters of this second domain of information privacy research with the intent of informing a wider debate about the entitlement to anonymity for customers who elect to use prepaid services over commercial networks.

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)0.003
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.872
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.002
Open science0.0030.001
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 head0.060
GPT teacher head0.392
Teacher spread0.332 · 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 designOther design
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

Citations9
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueConvergence The International Journal of Research into New Media TechnologiesSame topicPrivacy, Security, and Data ProtectionFrench-language works237,207