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Record W2618682770 · doi:10.5539/ibr.v10n6p259

Role of Internal Auditor in Dealing with Computer Networks Technology - Applied Study in Islamic Banks in Jordan

2017· article· en· W2618682770 on OpenAlexvenueno aff
Atallah Ahmad Alhosban, Mohammed Alsharairi

Bibliographic record

VenueInternational Business Research · 2017
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsAuditAccountingSample (material)Internal consistencyTest (biology)Internal auditConsistency (knowledge bases)IslamWork (physics)External auditorComputer scienceBusinessMarketingEngineering

Abstract

fetched live from OpenAlex

The aim of the study was to identify Role of internal auditor in dealing with computer networks technology - Applied study in Islamic banks in Jordan -. The objectives were to identify the role of the computer networks that are installed for the first time in addition to the role of the auditor in the physical components of computer networks and maintenance. The study community consists of internal auditors in Islamic banks or financial institutions, a total of 101 questionnaires were distributed and 89 questionnaires were retrieved for statistical analysis. A single sample test was used to test the hypotheses of the study. The arithmetic mean and the alpha test were used to find the internal consistency rate of the study sample. The most important results of the study: the presence of the impact of computer networks on the internal audit work environment both in the installation of the computer for the first time or provide the physical components of computer networks. The most important recommendations: The need to hold seminars and conferences using technology tools and their effects on the environment of internal auditing or external auditing or accounting environment in general.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score0.399

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.021
GPT teacher head0.313
Teacher spread0.292 · 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 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

Citations5
Published2017
Admission routes1
Has abstractyes

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