Une intervention éducative dans une communauté appauvrie : pistes à explorer pour une gestion durable des ressources
Bibliographic record
Abstract
Dans un contexte de crise environnementale qui affecte nos sociétés, il nous semble avant tout important d’éduquer la population à une nouvelle manière de penser et d’agir, afin qu’elle se mue en décideurs capables de faire des choix éclairés face aux situations complexes auxquelles les sociétés sont de plus en plus confrontées. Le présent article concerne une étude qui a été réalisée dans un souci d’identification des stratégies d’intervention éducative qui pourraient aider une communauté aux prises avec des problèmes de sécurité alimentaire et de survie, de continuer à combler ses besoins tout en posant, en même temps, des gestes de gestion durable de leurs ressources. La population ciblée est celle se trouvant dans un bassin versant d’un marais en dessèchement, le marais de Rugezi au Rwanda.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 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".