La construction d’une « Hyper Nature » dans les projets de la ville durable : le cas du Grand Paris
Bibliographic record
Abstract
Le concours du Grand Paris qui a rassemblé une partie importante du champ de l’architecture et de l’urbanisme ainsi que des centres de recherche en sciences sociales et en sciences dures sur la question de la ville durable, a vu l’accomplissement d’un certain nombre de représentations nouvelles concernant le rapport ville nature. Parmi celles-ci la volonté d’intensifier la présence objectale et processuelle de la nature afin de réguler, d’aménager, mais également de structurer l’espace urbain. L’article se propose de décrire les modalités d’action de cette « hyper nature » au travers de l’examen de certaines propositions du concours et de mesurer les écarts qu’elles constituent par rapport aux théories classiques de l’urbanisme.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.020 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".