Le parc amazonien de Guyane française et la mise en tourisme de la nature. L’intégration de la cogestion adaptative
Bibliographic record
Abstract
Les projets de conservation de grande envergure présentent des défis importants et exigent par le fait même d’adopter des approches multiscalaires et multidimensionnelles afin d’ajuster les pratiques. C’est le cas du parc Amazonien de Guyane française (PAG) qui présente de nombreux défis. L’approche de gouvernance que présente la cogestion adaptative apparaît alors comme un cadre adapté et prometteur dans l’analyse du cas du PAG afin d’orienter les pratiques et les décisions pour répondre au défi que représente la mise en œuvre de sa charte. Le développement du tourisme de nature sera analysé à travers le prisme de la cogestion adaptative en identifiant certaines conditions de succès dans la mise en œuvre de la charte du PAG.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".