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Record W2121543771 · doi:10.1017/s1074070800002662

Effects of Price and Quality Differences in Source Differentiated Beef on Market Demand

2009· article· en· W2121543771 on OpenAlexaboutno aff
Youngjae Lee, P. Lynn Kennedy

Bibliographic record

VenueJournal of Agricultural and Applied Economics · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomics of Agriculture and Food Markets
Canadian institutionsnot available
FundersCooperative State Research, Education, and Extension ServiceU.S. Department of Agriculture
KeywordsHanwooPrice elasticity of demandQuality (philosophy)Order (exchange)EconomicsWelfareConsumer demandAgricultural economicsBusinessBeef cattlePreferenceMicroeconomicsFood scienceAnimal scienceMarket economyChemistry

Abstract

fetched live from OpenAlex

In order to estimate demand elasticities of source differentiated beef in South Korea, this study used the quantity of an endogenous demand system derived through maximizing the economic welfare of market participants including local beef consumers and local and foreign beef suppliers. The demand system is then weighted with respect to quality adjustment parameters to identify the effects of quality differences in source differentiated beef on market demand. As implied by the high relative price of locally produced “Hanwoo” beef, substitutability between local and imported beef is shown to be very weak and the own price elasticity of South Korean beef is shown to be inelastic. Related to quality differences between source differentiated beef, South Korean beef consumers show a preference for Australian beef relative to U.S. and Canadian beef, perhaps due to BSE concerns.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.180
Teacher spread0.169 · 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

Citations4
Published2009
Admission routes1
Has abstractyes

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