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Record W3144746617

Правовое регулирование лоббизма и иные механизмы продвижения частных интересов

2009· article· ru· W3144746617 on OpenAlexaboutno aff
Масленникова Светлана Викторовна

Bibliographic record

VenuePravo. Zhurnal Vysshey shkoly ekonomiki · 2009
Typearticle
Languageru
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsnot available
Fundersnot available
KeywordsProtectionismPolitical scienceLegislaturePoliticsState (computer science)LawLegal pluralismLegislative processPluralism (philosophy)Law and economicsLegal researchPublic administrationBusinessSociologyLegal realismInternational trade
DOInot available

Abstract

fetched live from OpenAlex

The article investigates the limits of legal regulaton of lobbyism in a number of foreign countries (the USA, Canada, Lithuania, etc.). The lobbist activity submits not only to the rules of law, but also to the rules of ethical behaviour of officials, to the codes of a professional ethics of lobbyists. Lobbyism is connected with institutional conditions, vested in the system of functioning of authorities, and also depends on the state of development of other legal institutions elections, activity of political parties, political pluralism, legislative process. The many-sided social and legal nature of lobbyism predetermines problems with its legal grounding and practical implementation. Among limits of legal regulation of lobbyism one can mention the following: 1) it is impossibile to include into the law on lobbyism a lot of spheres of public relations; 2) the potential of noncommercial organizations is underestimated; 3) there are no obstacles for the international lobbyism; 4) it is impossible to resist to protectionism of authorities towards large national corporations, etc.

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: none
Teacher disagreement score0.020
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0200.007

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 head0.018
GPT teacher head0.231
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 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
Published2009
Admission routes1
Has abstractyes

Explore more

Same venuePravo. Zhurnal Vysshey shkoly ekonomikiSame topicInternational Arbitration and Investment LawFrench-language works237,207