Les dimensions de la sociologie économique de la finance : Perspective critique, transformations institutionnelles et facteurs collectifs
Bibliographic record
Abstract
Ce texte présente deux lectures des caractéristiques institutionnelles du capitalisme financier à travers l’étude des travaux de J. M. Keynes avant la crise de 1929 et les recherches de D. Mackenzie sur la conceptualisation et l’utilisation des produits dérivés aux États-Unis après la seconde guerre mondiale. Trois dimensions de leur travail seront mises en exergue : une critique d’une vision orthodoxe de la finance qui considère les marchés financiers comme un mécanisme efficace et transparent d’allocations des ressources ; une analyse des transformations institutionnelles de la sphère financière ; une explication de l’instabilité des marchés financiers centrée sur le rôle des facteurs collectifs. Les travaux de Keynes et de Mackenzie contribuent ainsi à mettre en lumière la nature sociale et politique des mécanismes qui sous-tendent le processus actuel de financiarisation des relations économiques.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".