Concurrence sur le marche des produits et couts de delegation
Bibliographic record
Abstract
Nous modelisons les effets de la concurrence du marche des produits sur les couts de delegation et y allons de deux grandes previsions d'ordre empirique. D'abord, la concurrence, en diminuant les couts de delegation, accroit nettement l'importance qu'attachent les entreprises a l'amelioration de la qualite, d'ou une plus forte incitation au rendement et, de ce fait, un accroissement de l'effort et de la qualite. Ensuite, ces effets s'accentuent en situation de gravite des problemes de delegation et devraient etre plus marques dans les grandes societes hierarchisees (ou ces problemes se posent avec plus de gravite) que dans les entreprises individuelles. Nous verifions les previsions de notre modele a l'aide d'un ensemble unique de donnees decrivant les caracteristiques tant des entreprises que de leurs salaries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 teacher head, 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".