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Record W2414563068 · doi:10.5430/afr.v5n3p1

Assessment of Compliance with OHADA Uniform Accounting Act by Public Limited Companies

2016· article· en· W2414563068 on OpenAlexvenueno aff
Michael Forzeh Fossung

Bibliographic record

VenueAccounting and Finance Research · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
Fundersnot available
KeywordsAccountingCompliance (psychology)BusinessLiabilityClosenessPublic disclosureInternational Financial Reporting StandardsIndex (typography)

Abstract

fetched live from OpenAlex

Francophone African countries have made a tremendous effort in harmonising domestic standards and reporting with the International Financial Reporting Standards (IFRS). Moving from two distinct OCAM streams to two OHADA streams (effective 1985) and now one OHADA Uniform Accounting Act embodying 17 member countries (effective 2001) is a milestone towards harmonisation of reporting practice both domestically and internationally. This empirical study examines whether the effort of harmonisation, especially after the 2001 standards has resulted in the successful convergence of firms' accounting practices by analysing public limited liability companies' compliance with the OHADA Uniform Accounting Act and if such compliance has improved over time. The study has been carried out using the 2008 and 2009 annual reports of three public limited companies in the OHADA zone that translate their financial statements into IFRS. The ranks of closeness and compliance index have been used to analyse data. Findings reveal a relatively high level of compliance with the accounting regulation by sampling limited liability companies. The results also give an indication of harmonisation in accounting practice of limited companies within member countries as they were found to be substantially consistent in compliance, especially in countries that have instituted the Statistics and Tax returns (or "DSF") as a reporting medium.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.392
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
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0000.001
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 head0.048
GPT teacher head0.302
Teacher spread0.254 · 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.

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

Citations3
Published2016
Admission routes1
Has abstractyes

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