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Record W2102626062 · doi:10.5539/jas.v7n12p107

Impact of Political Connection on Farming Households’ Performance of Tea Production in Vietnam

2015· article· en· W2102626062 on OpenAlexvenueno aff
Nguyen To‐The, Quoc Tran-Nam

Bibliographic record

VenueJournal of Agricultural Science · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPolitical Influence and Corporate Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsCommunismPoliticsAgricultureProduction (economics)Value (mathematics)Agricultural economicsPolitical scienceEconomicsEconomic growthGeographyMathematicsLaw

Abstract

fetched live from OpenAlex

<p><em>Purpose</em>: This paper aims to investigate the impacts of political connections on farming households’ performance, especially in tea production.</p><p>Methodology/Approach: The Box-Cox methodology is applied using the primary data surveyed on 244 tea farming households in Vietnam.</p><p><em>Findings</em>: The findings show the significant role of political connection on improving farming households’ income, particularly to members of the Communist Party, Youth Union and Farmer’s Union. However, the interaction effects of Farmer’s Union, Youth Union, Veteran’s Union and Communist Party with land has negatively significant impact on farming household income.</p><p><em>Practical Implications</em>: The evidences point out the capacity of improving tea producers’ income could be really potential implying most of existing related policies which should be adjusted.</p><p><em>Originality/Value</em>: This is the first research examining the impact of political connection on<em> </em>agricultural performance, especially in tea production. The impacts are estimated in de-tail; such as participating more on Veteran’s, Farmer’s, Youth Union and Communist Party may reduce time on cultivating; as a result, cultivated land could be reduced. Basing on these findings, we also suggest some appropriate policy implications related to the issue how to improve income of tea production households.</p>

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.378
Threshold uncertainty score0.181

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.003
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 head0.044
GPT teacher head0.279
Teacher spread0.235 · 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.

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

Citations4
Published2015
Admission routes1
Has abstractyes

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