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Record W2791640208 · doi:10.5539/ibr.v11n3p66

The Role of Forensic Accounting in Maintaining Public Money and Combating Corruption in the Jordanian Public Sector

2018· article· en· W2791640208 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Business Research · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicMethodology and Impact of Social Science Research
Canadian institutionsnot available
Fundersnot available
KeywordsForensic accountingAccountingLanguage changeAuditPublic sectorAccountabilityBusinessConvictionGovernment (linguistics)Money launderingPublic relationsPolitical scienceFinanceLaw

Abstract

fetched live from OpenAlex

The present study aims at stating the role and responsibility of the forensic accountant in the public sector as well as the challenges he/she faces in the attempt to reduce and detect fraud and corruption. A questionnaire consisting of 39 items was distributed among (100) employees of audit offices and firms, and another (30) among workers of the Accountability Bureau as an external control body that audits government units and departments.After analyzing and testing the hypotheses using SPSS, results show that forensic accounting has a role in reducing fraud and corruption in the public sector, and that the difference between the profession of forensic accounting and external auditing is of importance. This indicates a strong conviction from the part of respondents regarding the role of forensic accounting in maintaining public money and combating corruption.

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)0.030
metaresearch head score (Gemma)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.140
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0300.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.229
GPT teacher head0.480
Teacher spread0.251 · 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