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Record W4390484380 · doi:10.33002/jelp030301

Environmental Justice and Globalization: Putting a Focus on Indigenous Peoples and Local Community Rights and Perspectives

2023· article· en· W4390484380 on OpenAlexvenueno aff
Álvaro Augusto Sanabria-Rangel

Bibliographic record

VenueJournal of Environmental Law & Policy · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsnot available
FundersWorld Wildlife FundUnited States Agency for International DevelopmentWildlife Conservation SocietyU.S. Department of State
KeywordsIndigenousEnvironmental justiceIndigenous rightsEnvironmentalismPolitical scienceDenialGlobalizationBureaucracyEconomic JusticeState (computer science)Human rightsSociologyPolitical economyEnvironmental ethicsLawPolitics

Abstract

fetched live from OpenAlex

The right to participate in matters of local importance for communities as well as for Indigenous Peoples are increasingly recognized. This article analyses the continuous existence of deterrents to environmental justice from the perspective of social leaders who have worked in the defence of environmental and Indigenous rights in Colombia, Peru and Chile. This article argues that community rights and interests are relegated as a consequence of notions of development that are solely based on economic growth. This lack of a proper balance between a market-driven vision of development with local and Indigenous perspectives of development is manifested in different obstacles to effective participation and could also be explained by post-colonial dynamics. The research identifies seven particular obstacles that environmental and Indigenous rights defenders face to make their voices and perspectives be heard, namely: a total denial to binding mechanisms for participation, lack of information and transparency surrounding projects with a significant impact to local environments, unwillingness of State actors to supervise extractive industries, lack of access to environmental justice, lack of recognition by local authorities, in particular of Indigenous representatives, deception to the agreements between mining companies and the local communities as well as bureaucratic practices and judicial persecution, stigmatization and threats to the lives of environmental and Indigenous leaders.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.580
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
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 head0.015
GPT teacher head0.280
Teacher spread0.266 · 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.

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

Citations3
Published2023
Admission routes1
Has abstractyes

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