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Scale, networks, and information strategies: exploring indigenous peoples' refusal of a protected area in Suriname

2011· article· en· W2138628669 on OpenAlexaff
Bethany Haalboom, Lisa M. Campbell

Bibliographic record

VenueGlobal Networks · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicAnthropological Studies and Insights
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsIndigenousScale (ratio)PoliticsState (computer science)GeographyPolitical scienceEnvironmental resource managementPublic administrationEconomic growthLawCartographyEcologyComputer science

Abstract

fetched live from OpenAlex

Abstract In this article, we examine the response of three indigenous communities in western Suriname to the proposed establishment of a protected area on their traditional lands. In particular, we focus on how the transnational, national and sub‐national networks associated with indigenous rights and protected areas influenced the decision the communities made to reject the protected area. Central to the analysis are the concepts of scale, networks and information; we explore how a national indigenous rights organization used scale and networks to relay information strategically and empower communities in their decision‐making. However, while scale was an empowering political tool, it has also served to disempower indigenous peoples in Suriname through the continuing importance of the state in protected area implementation and legal claims to lands and resources.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.069
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.008
Scholarly communication0.0040.002
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 head0.044
GPT teacher head0.265
Teacher spread0.221 · 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

Citations14
Published2011
Admission routes1
Has abstractyes

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