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Record W4414326835 · doi:10.7202/1119569ar

Des familles rurales confrontées à la dégradation de l’environnement dans les oasis d’Asie centrale

2025· article· fr· W4414326835 on OpenAlexvenueno aff
Tommaso Trevisani

Bibliographic record

VenueAnthropologie et Sociétés · 2025
Typearticle
Languagefr
FieldEnvironmental Science
TopicRangeland Management and Livestock Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)South asiaRegional developmentRural development

Abstract

fetched live from OpenAlex

Basé sur des ethnographies de l’Ouzbékistan (Khorezm) et du Kazakhstan méridional (steppe de la Faim, delta du Syr-Daria), cet article décrit, contextualise et discute de la façon dont les familles rurales des oasis d’Asie centrale se sont adaptées aux conditions environnementales changeantes en s’appuyant de plus en plus sur les liens de parenté. Là où les conditions écologiques remettaient en question la viabilité des anciennes pratiques agricoles, les liens de parenté restaient importants dans la vie des gens lorsque les disparités sociales, l’insécurité économique et la vulnérabilité environnementale augmentaient. Partageant un passé soviétique commun, l’agriculture dans ces oasis suit aujourd’hui des voies divergentes en raison des différents cadres économiques et politiques des États indépendants. Cependant, quelles que soient les politiques adoptées, la dégradation de l’environnement est partout en hausse dans l’agriculture irriguée. Les pratiques agricoles ancrées dans la parenté ont parfois permis aux familles rurales de mieux s’adapter à des contextes environnementaux dégradés, mais ont parfois aggravé davantage les problèmes environnementaux préexistants. Toutefois, la parenté et les réseaux familiaux ont conservé une importance centrale pour faire face aux difficultés croissantes de l’agriculture irriguée en Asie centrale.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.072
GPT teacher head0.456
Teacher spread0.383 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

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