• LAVAL Christian , L’Homme économique. Essai surles racines du néolibéralisme , Gallimard, Paris, 2011, 416 p., 25,30 euros.
Bibliographic record
Abstract
L’économie expérimentale traite abondamment de la confiance et de la réciprocité, y compris dans des interactions de court terme. Cependant, la plupart du temps, les expériences menées examinent dans un cadre défini à l’avance si les individus ont tendance à se faire confiance et s’ils sont payés en retour pour leur éventuel « investissement » en autrui. Cet article se propose d’explorer si l’adoption d’une stratégie qui vise à modifier délibérément les règles de l’interaction au profit de l’autre agent est susceptible d’être bénéfique. Le propos n’est plus de savoir s’il est raisonnable d’accorder sa confiance à son interlocuteur mais devient plutôt d’agir de manière à lui inspirer confiance. À partir de là, une expérience particulièrement simple, fondée sur les travaux de Tversky et Shafir, s’efforcera de vérifier si la sécurisation des attentes de l’autre individu se traduit par une forme de reconnaissance de sa part et peut favoriser l’apparition de comportements qui reposent davantage sur la coopération.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".