GESTION DU RESULTAT ET INTRODUCTION EN BOURSE : CAS DES ENTREPRISES TUNISIENNES
Bibliographic record
Abstract
Ce papier étudie la gestion du résultat dans les entreprises tunisiennes non financières lors de leur introduction en bourse durant la période 1998-2003 en utilisant plus qu'un modèle d'estimation des accruals discrétionnaires. Nos résultats ne révèlent en moyenne, aucune gestion du résultat économiquement significative. Une analyse additionnelle, après l'exclusion des entreprises publiques, montre que les entreprises privées gèrent leur résultats à la hausse une année avant l'introduction et, conformément à Teoh et al (1998), ils continuent à le faire après l'introduction pour camoufler l'effet réversible d'une gestion antérieure et atteindre les objectifs optimistes assignés avant l'offre. L'étude met l'accent, aussi, sur l'effet réversible des accruals discrétionnaires et montre que les entreprises ne peuvent pas emprunter indéfiniment des gains futurs pour augmenter leurs gains actuels.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".