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Record W4297883601 · doi:10.1017/9781108667289.009

Reflections on a Political Ecology of Sovereignty

2022· book-chapter· en· W4297883601 on OpenAlexaboutno aff
Tyler McCreary, Vanessa Lamb

Bibliographic record

VenueCambridge University Press eBooks · 2022
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSoutheast Asian Sociopolitical Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSovereigntyCorporate governancePoliticsIndigenousPolitical ecologyState (computer science)Political scienceBureaucracyNatural resourceSociologyPolitical economyGeographyEcologyLawEconomicsManagement

Abstract

fetched live from OpenAlex

This chapter examines the relationships between representations and operations of sovereignty in natural resource governance. We advance a ‘political ecology of sovereignty’, examining the participation of non-state actors in resource governance processes. We particularly argue that processes of integrating subaltern populations through mapping local ecological knowledge can modify effective governance practices while nonetheless reproducing the legibility of state sovereign authority and its territorial boundaries. Exploring the Enbridge Northern Gateway pipeline in Canada, we suggest that state jurisdictional authority is secured through incorporating Indigenous interests as a delimited geography of tradition. Examining the Hatgyi hydroelectric development along the Thai–Myanmar border, we argue that the territorial boundaries of those nation-states are rearticulated through the governance of this transboundary development. Through these cases, we demonstrate how the insertion of local knowledge works not only to reconfigure effective governance processes but also to reinforce the effect of state sovereignty in new ways.

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)0.004
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.044
Scholarly communication0.0090.010
Open science0.0010.005
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0050.000

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 head0.064
GPT teacher head0.307
Teacher spread0.243 · 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 designTheoretical or conceptual
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

Citations0
Published2022
Admission routes1
Has abstractyes

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Same venueCambridge University Press eBooksSame topicSoutheast Asian Sociopolitical StudiesFrench-language works237,207