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Record W3115558446 · doi:10.38050/01300105201633

Aims and Tools of Competitive Policy in the Russian Metal Industry over the Past Quarter Century

2016· article· en· W3115558446 on OpenAlexaboutno aff
Dina Korneeva

Bibliographic record

VenueLomonosov Economics Journal · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Development and Digital Transformation
Canadian institutionsnot available
Fundersnot available
KeywordsDominance (genetics)Competition (biology)Stylized factInternational tradeHarmPosition (finance)BusinessQuarter (Canadian coin)EconomicsInternational economicsIndustrial policyPolitical science

Abstract

fetched live from OpenAlex

Paper is devoted to the analysis of impact of foreign trade and antitrust policies on development of competition and the position of domestic buyers of Russian metal products. It presents a stylized description of the development of the Russian metallurgy over 25-year period, considering the peculiarities of industry, which influence the problems of competition policy; paper describes the application of competition and foreign trade policies in the industry, taking into account relationships with industry structure. It illustrates the problem of trade-off between an increased competitiveness in world market and consumers protection within the country in relation to industries with the dominance of large exporters. The analysis revealed contradictions in pursued policy: approval of mergers that might restrict competition in the markets of metal products in Russia, and relatively high level of import protection are not consistent with regular investigations of violation of antitrust legislation by Russian metal producers, based on harm imposed to domestic consumers.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.031

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 studies0.0010.003
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.212
Teacher spread0.189 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

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