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Record W4380686734 · doi:10.46398/cuestpol.4177.11

Legal regulation of ethno-national policies (national minorities, indigenous peoples, multiculturalism)

2023· article· en· W4380686734 on OpenAlexaff
Yu. Ye. Kovnyі, Vadym M. Roshkanyuk, Alen V. Panov, Марія Вовк, Kateryna Dubova

Bibliographic record

VenueCuestiones Políticas · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean and International Law Studies
Canadian institutionsWeyerhauser (Canada)
Fundersnot available
KeywordsMulticulturalismIndigenousPolitical scienceLegislationLegislatureDemocracyMinority rightsPublic administrationIndigenous rightsPrismEmpowermentLawHuman rightsPolitics

Abstract

fetched live from OpenAlex

The current situation of national minorities, indigenous peoples and the policy of multiculturalism needs to be reconsidered from a legal point of view. The purpose of the article was to investigate the legal regulation of ethnonational policy, using the experience of major democratic states. The article used various methods of scientific knowledge such as cognition. On the basis of the analysis, the legal mechanisms of ethnonational policy regulation are examined in detail through the prism of the main trends of indigenous peoples' rights. In the results, special attention was paid to the practices of multiculturalism and observance of the rights of indigenous peoples. In particular, the founding documents of the UN and the Council of Europe, individual legislative decisions of other international organizations and various national parliaments were studied. Also, using the example of the legislation of modern countries of the Balkan Peninsula, modern trends in the resolution of the rights of national minorities are indicated. The conclusions underline the prospect of using the model of autonomous communities for the legal regulation of the life of national minorities and indigenous peoples in a multicultural society.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.947
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.056
GPT teacher head0.360
Teacher spread0.304 · 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 teacher head, 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

Citations0
Published2023
Admission routes1
Has abstractyes

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