L’implantation des aires protégées au vietnam : quels impacts pour les populations locales ? Une étude de cas dans la province de Lâm Đồng
Bibliographic record
Abstract
À partir des années 1960, le Vietnam, comme d’autres pays en Asie du Sud-Est, a amorcé la mise en place d’un réseau d’aires protégées, l’objectif étant d’assurer la conservation des écosystèmes forestiers et certains sites d’une grande valeur environnementale, historique ou culturelle. Toutefois, les forêts d’Asie du Sud-Est restent les plus densément habitées de la planète. La mise en place de parcs nationaux ou de réserves naturelles contribue à bouleverser le rapport au territoire des populations affectées : avec les nouvelles règles, les populations locales doivent ajuster leur mode de vie, le plus souvent en le transformant complètement. L’hypothèse qui constitue la ligne directrice de cet article s’articule comme suit : en Asie du Sud-Est, et particulièrement au Vietnam, la mise en place d’aires protégées contribue à marginaliser les populations qui habitent près ou sur le territoire où se situe l’aire protégée. Le parc national Bi Ðoup-Núi Bà, province de Lâm Đồng au Vietnam, sert d’étude de cas.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".