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Record W2975360424 · doi:10.5539/ass.v15n10p149

An Economic Analysis of Traditional Agriculture Products: The Case of Chicken in Thua Thien Hue Province, Vietnam

2019· article· en· W2975360424 on OpenAlexvenueno aff
Long Hoang Thanh, Thi Minh Hop Ho, Philippe Burny, Thomas Dogot, Nguyen Đang Hao, Philippe Lebailly

Bibliographic record

VenueAsian Social Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Systems and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsLivelihoodAgricultureProduction (economics)HueScale (ratio)GeographyAgricultural economicsSocioeconomicsBusinessAgricultural scienceEconomicsCartographyEnvironmental science

Abstract

fetched live from OpenAlex

Agriculture and traditional agriculture products plays a significant role in the livelihoods of smallholder farmers in developing countries, including Vietnam. Cost-benefit Analysis and a mixed methodology were applied to evaluate the economic performance of traditional chicken production in Thua Thien Hue province, Vietnam by region and scale. The data were drawn respectively from 64 sample households in Huong Thuy and Nam Dong district in 2017. The Cost-benefit analysis shows that Huong Thuy tends to have a lower production cost and thus a higher production benefit as compared to those of Nam Dong district. This study also indicates evidence of the importance of veterinary, mortality rate, scale of production and region on the performance of chicken farmer in the province.

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 score0.255
Threshold uncertainty score0.507

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.015
GPT teacher head0.237
Teacher spread0.222 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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