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Record W2088410632 · doi:10.1109/hicss.2010.312

Quality and Fairness of an Information Security Policy As Antecedents of Employees' Security Engagement in the Workplace: An Empirical Investigation

2010· article· en· W2088410632 on OpenAlexaff
Burcu Bulgurcu, Hasan Cavusoglu, Izak Benbasat

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInformation and Cyber Security
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBusinessCLARITYInformation securityCompliance (psychology)Quality (philosophy)Information qualityConsistency (knowledge bases)PsychologyInformation systemComputer scienceComputer securitySocial psychology

Abstract

fetched live from OpenAlex

This paper investigates the impact of the characteristics of information security policy (ISP) on an employee's security compliance in the workplace. Two factors were proposed as the antecedents of employees' security compliance: ISP Fairness and ISP Quality. ISP Quality is comprised of three quality dimensions--Clarity, Completeness, and Consistency. It is shown that ISP fairness has a strong positive effect on an employee's ISP Compliance. In addition, it is found that ISP quality does not only have a strong positive influence on an employee's ISP compliance but also have a strong influence on an employee's perceived ISP fairness. This study contributes to the literature by highlighting the importance of ISP characteristics; namely, ISP quality and ISP fairness as an organizational resource to enhance an organization's information security.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.345
Teacher spread0.317 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations22
Published2010
Admission routes1
Has abstractyes

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