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Record W1926412811 · doi:10.1111/isj.12080

Company information privacy orientation: a conceptual framework

2015· article· en· W1926412811 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInformation Systems Journal · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsQueen's University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsBusinessObligationConceptual frameworkInformation privacyKnowledge managementPrivacy by DesignPrivacy policyConceptual modelInformation systemEconomic JusticePublic relationsInternet privacyComputer scienceSociologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Abstract Contemporary organisations struggle to develop effective responses to the complex challenge of deploying sophisticated information technology systems in an era characterised increasingly by customer demands for privacy. In this paper, we develop a conceptual framework of Company Information Privacy Orientation that attempts to reconcile the differences between the organisation's information management objectives and its ethical and legal obligations to address customers' privacy. Control theory and justice theory are utilised to build an organisation‐level framework that is composed of a firm's ethical obligation to its customers, its customer information management strategy and its assessment of the risks to its business created by legal demands to provide customer information privacy. The four different types of company privacy orientation profiles that emerge from this conceptual framework are then discussed, along with implications for future research.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.942
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.018
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.055
GPT teacher head0.328
Teacher spread0.273 · 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