Pour une vision géopolitique de l’identification des risques dans les mégaprojets : le cas de la centrale nucléaire de Jaitapur en Inde
Bibliographic record
Abstract
Cet article s’intéresse à la façon dont le raisonnement géopolitique peut enrichir l’étude de l’analyse du contexte des entreprises participant aux mégaprojets dans une perspective d’identification des risques. En détaillant cette méthode d’analyse particulière et au travers de l’analyse du cas de la centrale nucléaire de Jaitapur en Inde, il met en avant l’intérêt de détailler les chaînes relationnelles entre les risques eux-mêmes en raisonnant en termes de territoire, de représentation, de création de déséquilibre ou de rupture d’équilibre grâce à une observation multiscalaire et multi disciplinaire. Il appelle au développement d’une géopolitique des mégaprojets afin de minimiser les risques d’investissement.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".