Bibliographic record
Abstract
The Serial Cost Sharing Rule was originally conceived for situations where the demands of agents pertain to a homogeneous private good, produced by an unreplicable technology. In this context, it is endowed with a variety of desirable equity and coherency properties. This paper investigates the extension of this rule to the context where agents request many goods that may be public, private or specific to some of them, where the aggregation rule may be very general and where demands may have to be scaled in a non proportional way, more precisely along a path, in order to compute cost shares. It proposes the Path Serial Rule to address these general problems. It then shows which properties and characteristics are satisfied by this rule. Some of them are transposed directly from the single good context to the general one while other must be weakened. More precisely, they are required to hold only on the paths along which demands must be scaled if needed. Nevertheless, some of the characterisations of the serial rule in the single good case do not carry over to the general context. La règle de partage séquentiel des coûts a été conçue à l'origine pour le cas où les demandes des agents portent sur un bien privé homogène, produit par une technologie non reproductible. Dans un tel contexte, cette règle satisfait de nombreuses propriétés d'équité et de cohérence. Dans cet article, on étudie l'extension de cette règle aux cas où les demandes des agents peuvent être des vecteurs qui ne représentent pas forcément des biens homogènes entre les agents, dont l'agrégation ne se fait pas uniquement via la sommation et où les demandes doivent être ajustées de manière non proportionnelle, plus précisément le long d'un sentier, pour le calcul des parts de coût. On montre ensuite quelles sont les propriétés qui sont satisfaites par cette règle ou qui la caractérisent. Certaines sont transposées directement du contexte à un seul bien au contexte général alors que d'autres doivent être affaiblies. Plus précisément, on exige leur respect uniquement le long des sentiers servant à ajuster les demandes le cas échéant. Néanmoins, certaines caractérisations de la règle séquentielle dans le contexte à un seul bien ne peuvent pas être transposées au contexte général.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".