Bibliographic record
Abstract
Il n’est guère de concept plus commun ou élémentaire en analyse économique que celui de marché. Et pourtant il donne encore lieu à de profondes divergences de vues. Pour certains, le marché s’étend à l’univers tout entier, pour d’autres aux frontières des zones de libre-échange ou de marchés communs. Cet article soutient au contraire que l’étendue d’un marché est une question essentiellement empirique dont la réponse, variable, tient aux caractéristiques des produits concernés et aux conditions des échanges. Un marché parfait se définit par l’unicité du prix d’un bien homogène disponible à un même moment en un même endroit. Toutes les restrictions à cette notion de référence restreignent les aires du marché et ces restrictions varient à l’infini suivant les circonstances, les produits ou les facteurs de production. Certains marchés ne s’étendent pas au-delà d’un quartier urbain ou d’un village de campagne, d’autres, au contraire, rejoignent toutes les capitales du monde, comme c’est le cas du marché boursier.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.019 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 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".