Bibliographic record
Abstract
Ce travail de recherche vise a identifier, d'une part le comportement comptable des dirigeants de la societe initiatrice d'une operation de fusion acquisition et d'autre part les determinants de ce comportement comptable. Les contributions de cette these sont d'ordre theorique, methodologique et managerial. Sur le plan theorique, cette these permet de completer les travaux anterieurs s'inscrivant dans le cadre des prolongements de la theorie politico contractuelle dans un contexte specifique a savoir les fusions-acquisitions. Outre la detection de la gestion des resultats, ce travail s'interesse a l'etude de ses determinants notamment les determinants contextuels qui sont rarement testes. Sur le plan methodologique, cette recherche presente un double interet. Premierement, elle commence par une etude du cas clinique, Sagem-Snecma, pour tester l'existence de la gestion de resultat dans ce contexte particulier, puis la generaliser sur l'echantillon d'entreprises francaises sur la periode 2001-2007. Deuxiemement, cette these, utilise un modele de mesure de gestion des resultats, qui n'a pas ete utilise dans le contexte du fusion-absorption (modele du Dechow et al (2003)) et le compare avec le modele de Jones modifie. Sur le plan managerial, cette recherche permet aux utilisateurs de l'information comptable lors d'une operation de fusion-acquisition de mieux interpreter les etats financiers des societes participantes a l'operation. Elle peut contribuer aussi a faire avancer les reflexions des normalisateurs quant aux dispositions reglementant ces operations en revelant l'ampleur des choix comptables.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.006 |
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".