La GIZC à l’épreuve du terrain : premiers enseignements d’une expérience française
Bibliographic record
Abstract
Le fondement de la Gestion Intégrée des Zones Côtières (GIZC) peut se résumer à l'application sur le littoral des principes du développement durable. La GIZC est aujourd'hui d'une grande actualité puisque la recommandation européenne du 30 mai 2002, demandant à chaque État membre d'établir sa stratégie nationale, est arrivée à échéance en 2006. La France a rendu son rapport, mais au-delà de la stratégie, la GIZC soulève de nombreuses interrogations sur l'incidence réelle de cette nouvelle approche du littoral. Les réponses à un appel à projet national "¨Pour un développement équilibré des territoires littoraux par une GIZC", lancé en 2005 par l'État vers les acteurs du littoral, offre l'opportunité d'étudier la GIZC "en action". Ainsi, l'analyse de 49 dossiers déposés permet de dessiner provisoirement des freins et des pistes d'avancées du processus de mise en place de la GIZC par des "acteurs praticiens" du littoral aujourd'hui en France.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.016 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".