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Record W7097071282

Selected Paper Joint 2004 Northeast Agricultural and Resource Economics Association and Canadian Agricultural Economics Society Annual Meeting

2015· article· en· W7097071282 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetically Modified Organisms Research
Canadian institutionsnot available
Fundersnot available
KeywordsCredibilityDistrustAgricultureValue (mathematics)Socioeconomic statusPublic opinionChinaAgricultural biotechnology
DOInot available

Abstract

fetched live from OpenAlex

The study applies multivariate statistical and econometric tools to estimate the importance of the various factors driving Korean consumer acceptance of GM food products. The evidence thus far on biotechnology is decidedly mixed: public perceptions of food biotechnology are characterized by ongoing tension between opposing forces. The south Korean perceptions about food in general and ranges from excitement about the promise of environmental and economic benefits from GM products to fear and distrust of the technology for unknown risks. This highlights the importance of credibility of private and public institutions responsible for certifying the safety of GM foods and implementing necessary regulatory controls on GM processes and products. In between, many people are undecided, trying to learn more about the issues and reach a definitive position. Encouraging though is that some people are eager to try new foods. Koreans strongly favors food naturalness, familiarity, and access just as the west countries. Results suggest that the South Korean Consumer priorities with respect to various biotechnology and general food issues are related to their socioeconomic and value attributes. This implies that, at least in the near term, there will be considerable divergence within the

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 score0.578
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.017
GPT teacher head0.183
Teacher spread0.166 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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