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Record W3118648417 · doi:10.3390/land10010058

Tracing Agricultural Land Transfer in China: Some Legal and Policy Issues

2021· article· en· W3118648417 on OpenAlexaff
Chao Zhou, Yunjuan Liang, Anthony M. Fuller

Bibliographic record

VenueLand · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicChina's Socioeconomic Reforms and Governance
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPeasantAgrarian societyChinaLand tenureRestructuringAgricultural landContext (archaeology)Land managementLand lawAgricultureBusinessEconomic growthNatural resource economicsEconomicsEconomic systemGeographyPolitical scienceLawFinance

Abstract

fetched live from OpenAlex

This paper traces the evolution of land tenure changes in contemporary China since 1949. The transfer of land from peasant households to family farms and commercial sized units is on a vast scale and forms one of the greatest land reforms we have ever seen. The agrarian question forms both the policy and academic context in which this legislative account of land transfer is assessed and raises the question of whether land assembly in China resembles previous agricultural transformation policy and processes in industrialized countries or to what extent it has special characteristics of its own. The security of land holding in rural China, established with the household responsibility system, is seen to mature slowly over three to four periods of adjustment, always protecting the rights of peasants while improving conditions for increasing land productivity, resulting in an extension of the two rights of peasant holdings to three rights in the new millennium. The introduction of a third right, a land management right which is transferable from peasants to outsiders, has enabled a huge land assembly movement affecting millions of small holdings. This process of land tenure restructuring raises such questions as the consequences of the capitalization of agriculture, peasant land dispossession, proletarianization, and the prospect of a future land market in rural China, all topics for further research.

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)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.242
Threshold uncertainty score0.481

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.009
Science and technology studies0.0040.007
Scholarly communication0.0030.005
Open science0.0010.002
Research integrity0.0020.001
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 head0.007
GPT teacher head0.267
Teacher spread0.261 · 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 designQualitative
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

Citations56
Published2021
Admission routes1
Has abstractyes

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