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Record W2995348885 · doi:10.31857/s268667300007685-3

Agrarian Policy of the State in Russia and the U.S.: Comparative Analysis

2019· article· en· W2995348885 on OpenAlexaff
Oleg Ovchinnikov

Bibliographic record

VenueUSA & Canada Economics – Politics – Culture · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Development and Policies
Canadian institutionsInstitute for Christian Studies
Fundersnot available
KeywordsAgrarian societyAgricultureState (computer science)Agricultural policyState policyGovernment (linguistics)ImperfectEconomic policyRussian federationEconomic systemPolitical scienceBusinessEconomicsGeography

Abstract

fetched live from OpenAlex

At the present stage of development of the agricultural sector of the economy, state regulation measures play an increasing role as one of the most important conditions for its stability and progress. Over the past more than 200 years, and especially since the 1930s, the United States has established a highly effective system of agricultural policy. In many ways, thanks to its, the United States is now the recognized leader of world agriculture. The agricultural sector of Russia, despite almost 30 years of market reforms, is in a very controversial state – evident achievements are accompanied by a number of chronic problems. According to the author, the responsibility for this state lies in a large extent on the imperfect nature of the agricultural policy implemented by the Government of the Russian Federation. This paper compares various aspects of the organization of agricultural policy in Russia and the United States, identified inconsistencies in the basic principles of the organization of the optimal system of state regulation of the agricultural sector, proposed recommendations for their elimination.

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)0.000
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 score0.430
Threshold uncertainty score0.253

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.007
GPT teacher head0.182
Teacher spread0.175 · 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
Published2019
Admission routes1
Has abstractyes

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