MétaCan
Menu
Back to cohort
Record W196975415

The fourth dimension of information system audit and security

2009· article· en· W196975415 on OpenAlexaff
Akshai Aggarwal, Sujata Kanhere, Vishnu Kanhere, Shankar Kanhere

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInformation and Cyber Security
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsAuditBusinessShareholderInformation security auditAccountingInformation technology auditDimension (graph theory)Metric (unit)FinanceComputer scienceInternal auditComputer securityInformation securityJoint auditMarketingMathematicsCorporate governanceSecurity service
DOInot available

Abstract

fetched live from OpenAlex

Information system audit and control methodologies have come a long way from a small beginning fifty years ago. In a competitive flat world, large non-governmental enterprises affect the society in so many ways that the failure of a large enterprise is not only an issue of interest to its shareholders or its employees but also to the society, at large. The global financial meltdown has shown that ordinary tax-payers have to step in to save such large enterprises by infusing public funds. Today there is no objective metric to measure whether an enterprise has behaved responsibly and whether public funds should be used to save it. In this paper, the authors have proposed that the annual system audit/security function for an enterprise should be expanded to include a focused report on how socially responsible the enterprise has been during the year. The authors have developed a metric, based on Millennium Development Goals for measuring the social responsibility component in the working of an enterprise. The authors propose that this metric be used as the fourth dimension for IS Audit and Security to annually evaluate every enterprise.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.957
Threshold uncertainty score0.108

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.005
GPT teacher head0.196
Teacher spread0.191 · 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 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

Citations2
Published2009
Admission routes1
Has abstractyes

Explore more

Same topicInformation and Cyber SecurityFrench-language works237,207