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Record W3121906819

NEW MEASURE OF STATE SUPPORT FOR IMPORT SUBSTITUTION IN RUSSIAN AGROINDUSTRIAL COMPLEX

2015· article· en· W3121906819 on OpenAlexaboutno aff
Ekaterina Gataulinа

Bibliographic record

VenueRussian Economic Developments · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Development and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsSubsidyAgricultureSubstitution (logic)CommodityEuropean unionBusinessAgricultural economicsInternational tradeState (computer science)Food productsEconomic policyEconomicsInternational economicsMarket economyFinanceChemistryGeographyFood science
DOInot available

Abstract

fetched live from OpenAlex

The issue of using domestic over imported goods (import substitution) and adjusting accordingly the agricultural policy has become critical following the Russian food import ban on specifi ed types of agricultural products, commodities and food products from the United States, the European Union, Canada, Australia and Norway, and due to deteriorated relations with Ukraine and Moldova. New sub-programs have been added to the State Program for Development of Agriculture and Regulation of Agricultural Commodity and Food Markets so that import substitution can be accelerated. However, none of the new sub-programs has happened to foster import substitution. In some cases (e.g., subsidies for purchases of pedigree seeds, raw materials), the eff ect has been quite the opposite of what was supposed to be. Funding has been cut almost for all sub-programs to the extent that it is incomprehensible that development of respective industries has been announced as a priority and how the targets can be achieved. The foregoing suggest that the Russian agricultural policy need to be adjusted and updated.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.075
GPT teacher head0.252
Teacher spread0.178 · 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 designNot applicable
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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