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Analytical Review of Law Enforcement Practice to Identify Violations of Antimonopoly Legislation During Procurement Procedures by Certain Types of Legal Entities

2022· article· en· W4211104196 on OpenAlexaff
D. В. Ognevskaya

Bibliographic record

VenueRussian competition law and economy · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEconomic and Technological Systems Analysis
Canadian institutionsNickel Institute
Fundersnot available
KeywordsLegislationProcurementBusinessCall for bidsLimitingCompetition (biology)LawEnforcementSupreme courtGovernment procurementLaw and economicsPolitical scienceEconomicsMarketingEngineering

Abstract

fetched live from OpenAlex

New standards of proof in cases of violations of antimonopoly legislation during tenders, formed on the basis of the positions of the Supreme Court of the Russian Federation, imply a qualitatively new level of analysis of the content of documents regulating procurement activities of customers and capable of limiting competition. Customers, in turn, are required to regularly monitor their own procurement activities for the validity of the requirements contained in such documents and, in particular, cases of purchases from a single supplier.

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)0.020
metaresearch head score (Gemma)0.047
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: none
Teacher disagreement score0.030
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.047
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0300.016
Science and technology studies0.0020.004
Scholarly communication0.0050.004
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.249
Teacher spread0.237 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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