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Record W2040074660 · doi:10.1080/08941920309172

Racialization and Citizenship in Thai Forest Politics

2003· article· en· W2040074660 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

VenueSociety & Natural Resources · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicSoutheast Asian Sociopolitical Studies
Canadian institutionsYork University
Fundersnot available
KeywordsRacializationCitizenshipPoliticsIndigenousEthnic groupDevolution (biology)Identity (music)Stewardship (theology)Political scienceIndigenous rightsSociologyGender studiesLawAnthropologyEcology

Abstract

fetched live from OpenAlex

Abstract The first part of this article argues for the usefulness of the concept of racialization in understanding the intersection between identity and resource politics in Southeast Asia. The production of space through cadastral mapping, forest reservation, and community forests has all been racialized to the degree that these spaces are also associated with naturalized and essentialized ethnic identities. The second part explores the tension between racialization and citizenship in Thailand. Racialized ethnic minorities have used community forestry as a vehicle for claiming both more secure resource rights and for formal and substantive citizenship rights. The community forest movement in Thailand is not exclusionary on the basis of ethnic or indigenous identity, because of how it is based in expanding citizenship rights. Reliance on environmental stewardship criteria to justify resource rights could mean that upland peoples are subject to limits not experienced by lowlanders, whose activities have tremendous impacts on the environment.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.316
Threshold uncertainty score0.613

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.017
GPT teacher head0.294
Teacher spread0.277 · 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