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Record W2982353184 · doi:10.5430/ijhe.v8n7p138

Methods And Forms of Teaching of the Right To Information by Shareholders in the Digital Economy

2019· article· en· W2982353184 on OpenAlexvenueno aff
Aleksey I. Ovchinnikov, Yana B. Getman, И В Колесник, Veronika V. Kolesnik, Natalia A. Boyko

Bibliographic record

VenueInternational Journal of Higher Education · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSecurities Regulation and Market Practices
Canadian institutionsnot available
FundersRussian Foundation for Basic Research
KeywordsShareholderCorporate lawJoint-stock companyAccountingStock (firearms)Compliance (psychology)Law and economicsBusinessJoint (building)Corporate governanceLawPolitical scienceEconomicsFinanceEngineering

Abstract

fetched live from OpenAlex

Joint stock issues, i.e. legal rules governing relations within commercial corporations, attract special attention of researchers of private law, corporate law in particular. A large number of internal corporate contradictions plays a negative role in the economic and economic activities of joint-stock companies. This fact affects the growth in the number of scientific publications on the issues of shareholder relations between their participants in terms of compliance with the civil law prohibition of Teaching of the right. It also has an impact on judicial practice: more and more often, the courts use the term “Teaching of law” to analyze existing conflicts in corporate law.

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)0.005
metaresearch head score (Gemma)0.010
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 score0.014
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.009
Scholarly communication0.0050.006
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.002

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 head0.009
GPT teacher head0.309
Teacher spread0.300 · 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
Published2019
Admission routes1
Has abstractyes

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