MétaCan
Menu
Back to cohort
Record W2149229856 · doi:10.5539/ass.v10n23p135

Need for Government Regulation of Organic Foods

2014· article· en· W2149229856 on OpenAlexvenueno aff
Vladimir Zhidkov, Andrey G. Hramtsov, Zhanna V. Gornostaeva, Ekaterina Alekhina, Inna Kushnareva

Bibliographic record

VenueAsian Social Science · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDigitalization and Economic Development in Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsProduction (economics)Consumption (sociology)Organic productBusinessFood processingOrganic productionFood productsState (computer science)Government (linguistics)Organic farmingAgricultural economicsEconomicsFood scienceGeographyMicroeconomicsSociologyMathematicsChemistryAgricultureSocial science

Abstract

fetched live from OpenAlex

The authors define the concept of demand and prospects of organic foods, identify problems and prospects forthe production of organic foods in Russia, exploring features of state regulation of the production of organicfoods in different countries and justify the need for state regulation of the production of organic foods in Russia.The authors analyze the results of a sociological survey of 1,000 residents of the Volgograd region in age from20 to 60 years, determine the structure determination of respondents concepts of organic foods, the structure ofthe respondents 'opinions on the importance of regular consumption of organic foods, the structure of therespondents' opinions regarding the price for organic food, the structure of respondents 'opinions on thepercentage excess of the price for organic food over the price of conventional products, the structure of therespondents' opinions on the proportion of organic foods in the structure of the family budget, identify the mainpurposes of the production of organic foods, especially compared to the state support for Organic Agricultureeconomy in the countries of Western Europe, as well as classify the main types of environmental standards.

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)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.009
GPT teacher head0.197
Teacher spread0.188 · 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 designTheoretical or conceptual
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
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueAsian Social ScienceSame topicDigitalization and Economic Development in AgricultureFrench-language works237,207