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Record W2054785321 · doi:10.1525/ae.2007.34.2.303

Indigenous movements and the risks of counterglobalization: Tracking the campaign against Papua New Guinea's Ok Tedi mine

2007· article· en· W2054785321 on OpenAlexfundno aff
Stuart Kirsch

Bibliographic record

VenueAmerican Ethnologist · 2007
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
FundersUniversity of British ColumbiaUniversity of AucklandUniversity of MichiganGeorge Washington University
KeywordsIndigenousSubsistence agricultureNew guineaPolitical scienceSociologyGeographyEthnologyPolitical economyDevelopment economicsEconomicsEcologyArchaeologyAgriculture

Abstract

fetched live from OpenAlex

Many contemporary indigenous movements deploy strategies of counterglobalization that make innovative use of the architecture of globalization. This article examines an indigenous political movement that took legal action to gain compensation and limit the environmental impact of the Ok Tedi copper and gold mine in Papua New Guinea. Even though the campaign sought to balance the desire for economic benefits with the protection of local subsistence practices, its objectives were frequently misinterpreted. Indigenous movements that deviate from an antidevelopment position run the risk of being seen as greedy rather than green. Instead of reproducing allegories about the successful exercise of veto power over development projects, anthropologists need ethnographic accounts that analyze the complex ambitions of indigenous movements and the risks of particular strategies of counterglobalization.

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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

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 studies0.0040.004
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.278
Teacher spread0.251 · 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

Citations216
Published2007
Admission routes1
Has abstractyes

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