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Record W2002262409 · doi:10.4000/echogeo.13411

From resilience to viability: a case study of indigenous communities of the North Rupununi, Guyana

2013· article· fr· W2002262409 on OpenAlex
Andrea Berardi, Céline Tschirhart, Jayalaxshmi Mistry, Elisa Bignante, Lakeram Haynes, Grace Albert, Ryan Benjamin, Rebecca Xavier, Deirdre Jafferally

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEchoGéo · 2013
Typearticle
Languagefr
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsIndigenousResilience (materials science)GeographyEthnologyPolitical scienceHistoryEcologyBiology

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.600

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.104
GPT teacher head0.317
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it