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Record W1591023904 · doi:10.3917/eg.324.0289

L'agriculture russe après 10 ans de réformes : transformations et diversité

2003· article· fr· W1591023904 on OpenAlexaff
Т. Г. Нефедова, Denis Eckert

Bibliographic record

VenueL’Espace géographique · 2003
Typearticle
Languagefr
FieldSocial Sciences
TopicRegional Socio-Economic Development Trends
Canadian institutionsCanadian Nautical Research Society
Fundersnot available
KeywordsPolitical scienceHumanitiesMolecular biologyBiologyPhilosophy

Abstract

fetched live from OpenAlex

RÉSUMÉ En 1980, deux tiers des kolkhozes et des sovkhozes étaient déjà déficitaires. La situation ne s’est guère améliorée dans les dernières années de l’URSS et les réformes libérales ont profondément désorganisé un secteur fragile, dont la production s’est effondrée à partir de 1991. La distribution des terres entreprise en 1991-1993 a fait apparaître un très petit nombre de fermes indépendantes. Les fermes collectives antérieures se sont pour l’essentiel maintenues, malgré un changement de régime juridique. On est aujourd’hui dans un système complexe. Nombre de paysans des kolkhozes continuent à faire de l’agriculture vivrière ou commerciale sur leurs lopins, utilisant en partie les ressources de la ferme collective. Ils sont dans un statut mixte d’exploitant indépendant et de travailleur agricole. À cela s’ajoutent les différenciations spatiales qui révèlent que les différences intrarégionales sont plus fortes que les différences interrégionales. Les secteurs proches des grandes villes s’en sortent en général mieux que les régions périphériques, mais ce n’est pas vrai pour toutes les catégories d’exploitation.

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 score0.034
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.024
GPT teacher head0.259
Teacher spread0.235 · 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

Citations13
Published2003
Admission routes1
Has abstractyes

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