Terres gagnées et terres perdues : conséquences environnementales de l’essor de l’agro-industrie dans un désert de piémont. Le cas de l’oasis de Virú, Pérou
Bibliographic record
Abstract
Depuis les années 1990, le paysage des oasis rurales de la côte péruvienne est en pleine transformation. La surface agricole des vallées ne cesse de s’étendre et de nouveaux domaines agricoles s’implantent dans les interfluves désertiques. Le discours officiel du gouvernement péruvien met l’accent sur les aspects positifs de cette mutation des espaces arides en zones agricoles rentables et de la diversité des produits agricoles péruviens offerts sur les marchés internationaux. Quels en sont les impacts environnementaux au niveau local ?Après avoir présenté le paradoxe permettant au piémont côtier désertique d’être transformé en un espace agricole compétitif, cet article présente les impacts environnementaux qui affectent les acteurs locaux dans les vallées voisines des nouveaux périmètres irrigués.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".