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MODELS OF INVOLVEMENT OF INDIGENOUS PEOPLES IN POLITICAL DECISION MAKING PROCESSES

2024· article· en· W4405828868 on OpenAlexaboutno aff
Margarita Bukovska

Bibliographic record

VenueScientific and Analytical Herald of IE RAS · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousPoliticsDemocracyAutonomyGovernment (linguistics)Political scienceState (computer science)Indigenous rightsPolitical economyFace (sociological concept)Inclusion (mineral)Public administrationDevelopment economicsEconomic growthSociologyLawSocial scienceEconomics

Abstract

fetched live from OpenAlex

The article examines the experience of democratic countries in involving indigenous peoples in political decision-making processes. Since many indigenous peoples were subjected to discriminatory policies in the past, they had little chance to be heard. The article explores how countries and the global community have come to recognize the rights of indigenous peoples, including their political rights, and what models of inclusion of indigenous peoples in politics have become most popular in various democratic countries, specifically in Australia, New Zealand, Canada, Norway, Sweden, and Finland. The aim of the study is to examine the features of the models by which indigenous peoples are involved in political decision-making processes in democratic countries and to identify the factors influencing the choice of these models. The conclusion is that the most popular such models include the allocation of quotas in government bodies, creation of representative and consultative bodies, consultations with government agencies, as well as granting them territorial and non-territorial autonomy. It is emphasized that even in democratic countries, indigenous peoples still face difficulties in influencing politics and that the creation of special models is not always a guarantee of their full participation in political decision-making processes. One of the obstacles, in particular, is the persistence of discriminatory practices at some level towards indigenous peoples, which require resolution at the level of state policy.

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)0.000
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.478

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.045
GPT teacher head0.359
Teacher spread0.314 · 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
Published2024
Admission routes1
Has abstractyes

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Same venueScientific and Analytical Herald of IE RASSame topicArctic and Russian Policy StudiesFrench-language works237,207