Partage des coûts et tarification des infrastructures - Les méthodes de partage de coûts - Un survol
Bibliographic record
Abstract
In this paper, we present the different cost sharing methods one can find in the economic literature. We regroup the methods into three sets : the proportional methods, the cooperative game theory methods and the serial cost sharing methods. All those methods are presented through the stylized example of a pipeline connecting the Saguenay-Lac-Saint-Jean and Beauce regions to Montreal, through Quebec city, capable of satisfying the needs of those three regions. Dans le présent document, on entreprend une présentation systématique des méthodes de partage qu'on retrouve dans la littérature économique. On les regroupe en trois catégories : les règles de proportionnalité, celles qui sont inspirées de la théorie des jeux coopératifs et celles de répartition séquentielle (serial cost sharing). Chacune des méthodes présentées est illustrée à l'aide d'un exemple, celui d'un gazoduc qui relierait le Saguenay-Lac-Saint-Jean et la Beauce à Montréal, en passant par Québec, capable de desservir ces trois régions.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".