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Record W2606797709 · doi:10.4000/rga.3631

Soviet Legacy in the Operation of Pasture Governance Institutions in Present-Day Kyrgyzstan

2017· article· en· W2606797709 on OpenAlexfundno aff
Aiganysh Isaeva, Jyldyz Shigaeva

Bibliographic record

VenueRevue de géographie alpine · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland Management and Livestock Ecology
Canadian institutionsnot available
FundersGlobal Affairs CanadaNatural Environment Research CouncilSight Research UK
KeywordsPastureCitizen journalismCorporate governanceResource (disambiguation)Political scienceGeographyBusinessLawForestryComputer science

Abstract

fetched live from OpenAlex

The paper looks at the Soviet legacy in pasture governance systems of Kyrgyzstan that reproduce Soviet-era practices, meanings and power hierarchies. The study focuses on the current operation of local-level institutions (Pasture Users Associations and Pasture Committees) and the changing role of herders as a key pasture user category in the new socio-economic environment. Path dependence theory, which posits that old institutions continue to structure new policy arrangements, frames the analysis. Empirical data collected in Kyrgyzstan’s Naryn Province show how non-participatory decision-making and implementation modes, as well as the meanings surrounding pasture use, that were shaped during the Soviet era, still influence institutions in the present day, along with established patterns amongst resource users and between resource users and their environment.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.005
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.256
Teacher spread0.239 · 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

Citations11
Published2017
Admission routes1
Has abstractyes

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