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Record W4379621605 · doi:10.1126/sciadv.ade9557

Global impacts of extractive and industrial development projects on Indigenous Peoples’ lifeways, lands, and rights

2023· article· en· W4379621605 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScience Advances · 2023
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsMcGill University
FundersMinisterio de Ciencia e Innovación
KeywordsIndigenousLivelihoodLivestockAgricultureIndigenous rightsEnvironmental protectionEnvironmental justiceGeographyNatural resource economicsEnvironmental planningPolitical scienceEcologyLawEconomicsForestryBiology

Abstract

fetched live from OpenAlex

To what extent do extractive and industrial development pressures affect Indigenous Peoples' lifeways, lands, and rights globally? We analyze 3081 environmental conflicts over development projects to quantify Indigenous Peoples' exposure to 11 reported social-environmental impacts jeopardizing the United Nations Declaration on the Rights of Indigenous Peoples. Indigenous Peoples are affected in at least 34% of all documented environmental conflicts worldwide. More than three-fourths of these conflicts are caused by mining, fossil fuels, dam projects, and the agriculture, forestry, fisheries, and livestock (AFFL) sector. Landscape loss (56% of cases), livelihood loss (52%), and land dispossession (50%) are reported to occur globally most often and are significantly more frequent in the AFFL sector. The resulting burdens jeopardize Indigenous rights and impede the realization of global environmental justice.

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.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.646
Threshold uncertainty score0.250

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.018
GPT teacher head0.257
Teacher spread0.239 · 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