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Record W2384319798

Comparative study of domestic and foreign agricultural support policies

2013· article· en· W2384319798 on OpenAlexaboutno aff
Zheng Wen-tang

Bibliographic record

VenueJournal of Beijing University of Agriculture · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLand Rights and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsAgricultureProtectionismChinaDiversification (marketing strategy)BusinessContext (archaeology)Agricultural policyGlobalizationEconomic growthInternational tradeDevelopment economicsEconomicsPolitical scienceGeography
DOInot available

Abstract

fetched live from OpenAlex

Agriculture plays a fundamental role in national development.In the context of globalization,the developed countries have always been implementing powerful support and protection policies in a trend of diversification.The agricultural policies and its effects are highly related to a country's agricultural development.The agricultural support and protection policies in China has been implementing quite later than most of the developed countries,which has a quite long history of agricultural protectionism.We scanned the agriculture supporting policy systems of the USA,Canada,the EU and Japan through documentary analysis,and qualitatively compared the purpose and measures related to agriculture support policies between China and main developed countries.On summarizing the characteristics and experiences of developed countries,we suggested that China,as a big developing country with a large population,needs to establish its agricultural support policy according to the national conditions,clarify the purposes of agricultural support policy and optimize the related measures with the change of domestic and international environments.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.197
Teacher spread0.185 · 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 designNot applicable
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
Published2013
Admission routes1
Has abstractyes

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