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Record W1496554396 · doi:10.3968/5268

The Research of Urbanization, Industrialization and Agricultural Modernization's Effect on Food Security

2014· article· en· W1496554396 on OpenAlexvenueno aff
Jie Li, Hui Zeng

Bibliographic record

VenueStudies in sociology of science · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural risk and resilience
Canadian institutionsnot available
Fundersnot available
KeywordsUrbanizationIndustrialisationFood securityModernization theoryAgricultureChinaFood industryEconomic growthBusinessAgricultural economicsEconomicsEconomic systemPolitical scienceGeographyMarket economy

Abstract

fetched live from OpenAlex

Due to its large population, especially with the development of society and economy, China is in growing demand of food even it has long achieved food self-sufficiency. Food security relates to the national security, the problem of food security has been the focus of China. China’s industrialization, urbanization, and agricultural modernization process has a certain impact on food security, based on the empirical analysis of the correlation of the industrialization, urbanization and agricultural modernization. It’s said the industrialization and agricultural modernization has a positive effect on improving the level of food security, while the urbanization does the contrary. Under this circumstance, we propose to improve the industry nurturing agriculture, to promote agriculture with industry, science, to promote the urbanization level, and to improve the level of agricultural modernization.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.455
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.017
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.073
GPT teacher head0.349
Teacher spread0.276 · 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 teacher head, not a consensus.

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

Citations3
Published2014
Admission routes1
Has abstractyes

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