La contribution de la théorie des réseaux sociaux à la reconnaissance des opportunités de marché
Bibliographic record
Abstract
Les travaux de recherche sur l’entrepreneuriat se sont multipliés ces dernières années. Néanmoins, l’analyse de la genèse du projet de l’entrepreneur est relativement peu développée. Cette étude vise à tracer les lignes d’un programme de recherche focalisé sur les stades d’avant-projet et de démarrage de l’activité de l’entreprise. Après une première partie faisant le point sur la littérature théorique et empirique qui existe sur la phase de reconnaissance d’opportunité par l’entrepreneur, nous procédons à une mise en perspective à l’aide de la théorie des réseaux sociaux. Cette théorie, issue notamment des travaux de Burt et de Granovetter, permet de souligner le rôle des réseaux sociaux dans la détection et dans l’évaluation des opportunités entrepreneuriales et ouvre la voie à des études empiriques approfondies sur le comportement de l’entrepreneur.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".