L’équilibre concurrentiel comme limite de suites d’équilibres stratégiques de Stackelberg
Bibliographic record
Abstract
Dans cet article, nous considérons le modèle de Stackelberg stricto sensu (dans lequel chaque agent a une stratégie en quantités) mais en introduisant une hiérarchie de firmes. On sait que dans ce cas, c’est le rôle de meneur qui procure un avantage. Nous montrons dans le cadre d’un modèle linéaire à coûts moyens constants que plus le nombre de subordonnés d’un joueur est élevé, plus son profit est élevé. Cependant, lorsque le nombre de joueurs augmente, d’une part la répartition des niveaux de production et de profit reste fondamentalement inégalitaire, mais d’autre part la production totale de l’industrie tend vers la production d’équilibre concurrentiel, convergence préservée en présence de coûts fixes lorsque l’on réplique simultanément la taille au marché et le nombre de firmes, de sorte que, en termes de profits absolus, l’avantage que procure le rang disparaît.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".