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Record W3093679091 · doi:10.5267/j.ac.2020.10.012

The impact of governance on agricultural production as an exclusive factor of the country’s food security

2020· article· en· W3093679091 on OpenAlexvenueno aff
Gelena Pruntseva, Nazariy Popadynets, M. Barna, Ihor Stetsіv, Iryna Stetsiv, Valentyna Yakubiv, Lyudmila Shymanovska-Dianych, Yana Fedotova, Maria Karpiak, Iryna Hryhoruk

Bibliographic record

VenueAccounting · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Socioeconomic and Political Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsAgrarian societySubsidyAgricultureBusinessFood securityAgricultural productivityGovernment (linguistics)Production (economics)Corporate governanceInvestment (military)Agricultural economicsNatural resource economicsEconomic policyEconomicsMarket economyFinanceGeographyPoliticsPolitical science

Abstract

fetched live from OpenAlex

The agricultural production, due to the specificity of the functioning of the agricultural industry, is influenced by factors that have significant impacts on agricultural enterprises and determine the importance of state support. The unpredictable factors of agrarian production such as weather, natural disaster, and epidemics increase the risks of agricultural business. That is why farmers need to attract investments. But some farmers do not attract investment because of government subsidies. Besides, using government subsidies could have a negative impact on agrarian business. So, it is necessary to establish the effectiveness of governance for agricultural production and food security in general.

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 score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
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 head0.016
GPT teacher head0.229
Teacher spread0.213 · 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

Citations13
Published2020
Admission routes1
Has abstractyes

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