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Indigenous Movements in Latin America

2020· book-chapter· en· W3042201603 on OpenAlexaff
Roberta Rice

Bibliographic record

VenueOxford University Press eBooks · 2020
Typebook-chapter
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIndigenousLatin AmericansAutonomyIndigenous rightsPolitical scienceIdentity (music)State (computer science)Corporate governanceDecolonizationSociologyGender studiesLawPoliticsManagement

Abstract

fetched live from OpenAlex

Abstract What do Indigenous movement struggles in Latin America teach us about reconciling individual and collective rights? How are competing conceptualizations of the environment and development being addressed by states in the region? How are these tensions and contradictions playing out within Indigenous territories? This chapter provides answers to these questions by reviewing the main concepts, findings, and tensions in the literature on contemporary Indigenous movements in Latin America. It examines processes of Indigenous dispossession and resurgence; the struggle for identity, territory and autonomy; and the push for plurinationality and decolonization. It also addresses efforts to incorporate Indigenous ways of knowing and being into governance structures as a way to rebuild Indigenous-state relations on a more just foundation. The chapter concludes by outlining an emerging research agenda in the areas of implementing free, prior, and informed consent regimes; addressing gender dynamics in Indigenous movements; and adopting intersectional approaches to studying Indigenous movements.

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)0.001
metaresearch head score (Gemma)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.007
Scholarly communication0.0050.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.000

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 head0.025
GPT teacher head0.243
Teacher spread0.218 · 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
GenreOther

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

Citations3
Published2020
Admission routes1
Has abstractyes

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