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Record W2074544854 · doi:10.1163/15718115-01904005

Return of the Natives: Explaining the Development and Non-Development of Political Action by Indigenous Peoples in Democratic Political Systems

2012· article· en· W2074544854 on OpenAlexaboutno aff
Lee E. Dutter

Bibliographic record

VenueInternational Journal on Minority and Group Rights · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousPoliticsPolitical actionDemocracyContext (archaeology)PopulationPolitical scienceAction (physics)Political economyTerrorismCriminologyDevelopment economicsSociologyLawGeographyEcologyBiologyDemography

Abstract

fetched live from OpenAlex

Studies of individuals or groups who might use violence or terrorism in pursuit of political goals often focus on the specific actions which these individuals or groups have taken and on the policies which defenders (that is, governments of states) against such actions may adopt in response. Typically, less attention is devoted to identifying the relevant preconditions of political action and possible escalation to violence and how or why potential actions may be obviated before they occur. In the context of democratic political systems, the present analysis addresses these issues via examination of indigenous peoples, who typically constitute tiny fractions of the population of the states or regions in which they reside, in terms of their past and present treatment by governments and the political actions, whether non-violent or violent, which individuals from these peoples have engaged or may engage. The specific peoples examined are Aborigines and Torres Strait Islanders of Australia, Haudenosaunee of North America, Inuit of Canada, Maori of New Zealand, and Saami of Scandinavia.

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)0.002
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.005
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.315
Teacher spread0.292 · 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 designQualitative
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

Citations4
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal on Minority and Group RightsSame topicIndigenous Health, Education, and RightsFrench-language works237,207