From resilience to viability: a case study of indigenous communities of the North Rupununi, Guyana
Bibliographic record
Abstract
Le terme “résilience” a conquis une place importante dans le discours scientifique, et même à présent dans le langage courant. Or son utilisation reste souvent floue, puisqu’il peut être compris différemment : s’agit-il de résister ? De s’adapter ? De se transformer ? Cet article suggère l’utilisation d’un concept, la System Viability, ou la Viabilité des Systèmes. Ce concept permet d’appréhender six propriétés qui maximisent les chances d'un système de persister dans le temps, qu'il s'agisse d’écosystèmes ou de communautés. Dans cet article, nous appliquons et évaluons ce cadre conceptuel grâce à des méthodes visuelles participatives au sein de trois communautés indigènes du North Rupununi, au Guyana. Cet article tente de montrer que ce cadre conceptuel permet d’évaluer les stratégies de survie des communautés de manière cohérente et théoriquement corroborée, ce qui pourrait susciter l’intérêt de décideurs nationaux et internationaux en matière de résilience et durabilité.
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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 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".