Les villes-usines face à la problématique environnementale : réflexions à partir de l’exemple de l’agglomération dunkerquoise
Bibliographic record
Abstract
Fortement dépendantes de secteurs industriels en déclin ou disparus, les villes-usines sont confrontées depuis quelques années à des problématiques de reconversion et de (ré)attractivité. Dans ce cadre, la dimension environnementale, largement sacrifiée pendant les années de croissance, constitue un enjeu majeur, renforcé encore par la perspective de la transition écologique et sociale. Dans cet article, nous tentons de formuler quelques pistes de réflexion pour esquisser les contours d’une articulation de ces villes-usines à une reconsidération du rôle et de l’importance de l’environnement naturel dans le développement territorial. Pour cela, nous prenons appui sur l’exemple du territoire urbano-industriel de l’agglomération dunkerquoise, dont nous tirons des enseignements mis en perspective avec le cas particulier des villes-usines.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.022 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 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".