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Record W3112213664 · doi:10.6000/1929-4409.2020.09.185

The Economic Foundations of the Rule of Law in the Russian Federation

2020· article· en· W3112213664 on OpenAlexvenueno aff
Ivan Kuksin, Руслан Аллалыев, Valery Ivanonich Lipunov, Ilya V. Tyurin

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicLegal and Policy Issues
Canadian institutionsnot available
Fundersnot available
KeywordsRussian federationDialecticRule of lawLawRedistribution (election)Political scienceEconomic JusticeLaw and economicsSociologyEpistemology

Abstract

fetched live from OpenAlex

This study, based on the economic and legal metrics of the Russian Federation, considers the possibility of implementing the concept of the rule of law in the modern world. The study emphasises the issue of the rule of law in any country being directly related to the problem of redistribution of public goods. In many ways, this can be considered an example of how economic stability ensures legal stability. The research methodology includes a dialectical method, which allowed to ensure compliance with the principles of scientific knowledge. The study shows the dynamics of ensuring human rights, the distribution of income and expenses in society over different periods in the history of the Russian Federation. In this regard, the authors come to the conclusion that the perception and functions of the concept of the rule of law will soon deviate from classical liberal values towards the basic ideas of social equality and justice.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.021
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.010
Scholarly communication0.0060.002
Open science0.0000.002
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 head0.106
GPT teacher head0.395
Teacher spread0.289 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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