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Record W1890033775 · doi:10.7202/018887ar

Réformes de l’économie et changements agraires dans le delta du Fleuve Rouge au Vietnam

2008· article· fr· W1890033775 on OpenAlexvenueno aff
Lê Thị Vân Huệ

Bibliographic record

VenueAnthropologie et Sociétés · 2008
Typearticle
Languagefr
FieldSocial Sciences
TopicVietnamese History and Culture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesGeographyArt

Abstract

fetched live from OpenAlex

Cet article explore les théories de la différenciation à travers l’étude des effets des changements au niveau macro sur la différenciation agraire dans un village côtier du delta du Fleuve Rouge, au nord du Vietnam. Il s’agit d’une contribution au débat sur la différenciation agraire dans les sociétés postsocialistes en argumentant que, dans les endroits où l’économie de marché est devenue plus développée et qui sont proches des marchés des villes, les changements au sein des macrostructures accentuent les différences de revenu, altèrent les bases et les mécanismes de la différenciation, aussi bien que les modèles de différenciation existants. Je démontre que, si l’attention est portée sur les histoires et les contextes locaux, les études au niveau local contribuent à une meilleure compréhension des causes et des conséquences des changements agraires.

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)0.002
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 score0.175
Threshold uncertainty score0.347

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.003
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.173
GPT teacher head0.478
Teacher spread0.305 · 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
Published2008
Admission routes1
Has abstractyes

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