Impact de l’audit externe sur la qualité du résultat comptable : cas des entreprises tunisiennes cotées
Bibliographic record
Abstract
Cet article vise à examiner l’importance du rôle de contrôle exercé par l’audit externe sur la fiabilité des états financiers dans les entreprises tunisiennes cotées. Plus précisément, nous étudions l’impact de la qualité de l’auditeur externe sur la qualité du résultat comptable. Nous avons choisi la qualité des accruals et la pertinence comme mesure de la qualité du résultat comptable. À partir d’un échantillon de 108 observations sur la période 2000-2005, nos résultats confirment l’hypothèse selon laquelle les « BIG » et le secteur de spécialisation de l’auditeur améliore la qualité du résultat comptable. Les résultats montrent aussi l’existence d’une association significativement positive entre la durée de la relation d’audit et la qualité du résultat comptable.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".