Bibliographic record
Abstract
Book reviewed in this article: Stratégie et sociologie de l'entreprise. Rôle de la direction, comportement organisationnel, management et lien social Claude Michaud et Jean‐Claude Thoenig. (2001). Stratégie et esprit de finesse. L'apport des sciences économiques et sociales au management stratégique Guy Chassang, Michel Moullet, et Roland Reitter. Résumé Confrontés à la pratique de terrain, les intervenants, qu'ils soient chercheurs ou consultants, ont besoin de s'appuyer sur des théories qui leur permettent d'analyser l'écart—ou le jeu (slack) entre la prescription—ou les discours du management—et l'exécution—c'est‐à‐dire les pratiques réelles de gestion. Pour cela, il est une tendance féconde consistant à articuler des approches considérées parfois comme étant antinomiques: approches de type stratégique et approches de type sciences humaines et sociales (sociologie des organisations, psychologie, etc.). Dans le premier livre, un économiste et un sociologue (tous deux professeurs à l'INSEAD de Fontainebleau) s'adressent principalement aux managers en leur disant en quelque sorte: connaissez les langages qui traversent votre entreprise et vous serez à la hauteur de votre métier de dirigeants. Le second livre prend davantage le point de vue de consultants (Chassang est un des patrons d'Accenture‐France—ex‐Andersen Consulting) qui désirent participer au diagnostic de situations plutôt que se limiter à présenter des solutions. Ces ouvrages ont le mérite de s'appuyer sur des cas concrets. Abstract When confronted with fieldwork, the intervening parties, whether they be researchers or consultants, need to draw on theories that enable them to analyze the slack between prescription—or managerial discourse—and execution, i.e. real practices. For this purpose, they can rely on a fruitful trend that consists of articulating approaches that can be considered (to be) antinomic. The combination of strategic approaches with approaches based on humanities and social sciences—sociology of organizations, psychology, etc.—is the main interest of these two books. In the first book, an economist and a sociologist (both professors at INSEAD in Fontainebleau) aim at managers and recommend that they learn the languages used in their companies so they will be up to their functions as leaders. The second book focuses more on the views of consultants (Chassang is the head of Accenture France—formerly Andersen Consulting) who wish to take part in the diagnosis of situations rather than just foresee solutions. The great merit of these books is that they are based on actual cases.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.335 | 0.295 |
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".