L’écologie industrielle et territoriale : expérimentation opportuniste ou action collective favorable à une transition écologique
Bibliographic record
Abstract
Apparue vers la fin des annees 1980, l’ecologie industrielle propose un decouplage de la croissance economique et de l’epuisement des ressources naturelles au travers d’echanges de flux de matieres, d’energies, d’eau et d’equipements, etc. entre entreprises. Si, longtemps, les synergies industrielles furent decrites comme spontanees, relevant de la volonte de quelques acteurs industriels, les recentes recherches illustrent des demarches plutot planifiees et construites collectivement autour d’acteurs territoriaux, articulant strategies et ressources, interactions sociales et echanges techniques. Cet article propose une articulation entre l’ecologie industrielle et des enjeux de transition energetique d’une part, mais aussi son appropriation par des acteurs territoriaux. Au travers d’une analyse documentaire et une mise en recit de discours issus d’entretiens d’acteurs des synergies industrielles de Kamouraska (Canada-Quebec) et de Dunkerque (France), l’article renvoie a des determinants clefs de l’institutionnalisation de l’ecologie industrielle, mais aussi aux processus socio-organisationnels de sa mise en œuvre, capables d’en faire un « probleme public ».
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".