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Local Governments’ Behaviors Study on the Improvement for Farmers’ Cleaner Production in Factor Markets

2009· article· en· W1545914773 on OpenAlexvenueno aff
Hong Chen

Bibliographic record

VenueCanadian social science · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic theories and models
Canadian institutionsnot available
Fundersnot available
KeywordsAgricultureProduction (economics)Cleaner productionSustainable developmentBusinessChinaAgricultural productivityEconomicsEconomic systemPolitical scienceEngineeringMicroeconomicsGeography

Abstract

fetched live from OpenAlex

Both in developed and developing countries, governments of all levels pay much attention to the weak industry----agriculture and try their best to find out the effective way to develop it. Cleaner production in agriculture is the effective way to realize sustainable development in China. According to the behavioral features of local governments and the actuality of agriculture development, the thesis holds that the realization of agricultural cleaner production depends on the interest games between economic bodies and perfect market system. Besides, set up the operation mechanism for agricultural products and factor markets will help the development of cleaner production. Local governments allocate the resources by controlling all kinds of markets. The thesis mainly discusses the local governments’ behavior models based on factor markets. Adjust the farmers’ production behaviors with the constraints of capital, lands, labor and so on. Optimize combination between multi-items. Local governments will influence farmers’ choice by changing their production functions. The thesis also analyzes how can local governments accelerate the process of agricultural cleaner production and improve competitive power in local areas by influencing the management environment of agricultural products’ producers. Key words: Local governments, Factor markets, Target functions Resume: Tant dans les pays developpes que dans les pays en developpement, les gouvernement de toutes les echelles pretent attention a l’industrie faible --- agriculture, et font leur possible pour trouver le moyen efficace du developpement agricole. La production propre dans l’agriculture est une voie efficace pour realiser le developpement durable en Chine. Selon les caracteristiques comportementales des gouvernements locaux et l’actualite du developpement agricole, le present essai pense que la realisation de production propre agricole depend du jeu d’interet entre les corps economiques et du systeme parfait du marche. En plus, instituer le mecanisme operationnel pour les produits agricoles et les marches de facteur aidera au developpement de la production propre. Les gouvernements distribuent les ressources en controlant toutes sortes de marches. L’article traite essentiellement les modeles comportementaux des gouvernements locaux bases sur les marches de facteur : ajuster les comportements productifs des paysans avec les contraintes de capital, de terre, de labeur, etc ; optimiser la combinaison de multi-articles. Les gouvernements locaux vont influencer le choix des paysans en changeant leurs fonctions de production. L’article analyse aussi comment les gouvernements locaux peuvent accelerer le processus de la production propre agricole et elever la competitivite dans des regions locales en influencant l’environnement de management des producteurs agricoles. Mots-Cles: gouvernements locaux, marche de facteur, fonctions cible

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.030
GPT teacher head0.235
Teacher spread0.205 · 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
Published2009
Admission routes1
Has abstractyes

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