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Record W2979423128

Resurging through Kishiichiwan: The spatial politics of Indigenous water relations

2018· article· en· W2979423128 on OpenAlexaffabout
Michelle Daigle

Bibliographic record

VenueDecolonization: Indigeneity, Education & Society · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIndigenousColonialismPoliticsCorporate governancePolitical sciencePolitical economyNexus (standard)GeographyEconomySociologyLawEcologyEconomics
DOInot available

Abstract

fetched live from OpenAlex

In this paper, I center Indigenous water governance at the nexus of extractive capitalist development, water contamination and dispossession, and Indigenous self-determination. I do so by focusing on colonial capitalist legacies and continuities that are unfolding on Mushkegowuk lands of what is otherwise known as the Treaty 9 territory in northern Ontario, Canada. Through a spatial analysis, I trace contemporary forms of water dispossession through mining extraction to the larger colonial-capitalist objectives of the original signing of the James Bay, or Treaty 9, agreement. I argue that the colonial capitalist dispossession of water, through the seizing of land and interconnected waterways, and through the accumulation of pollution and contamination, is inextricably linked to larger structural objectives of securing access to Mushkegowuk lands for capitalist accumulation, while simultaneously dispossessing Mushkegowuk peoples of the sources of their political and legal orders. I end by discussing how Mushkegowuk peoples are resurging against settler colonial and capitalist regimes by regenerating their water relations, and how water itself cultivates a particularly spatial form of resurgence that regenerates Indigenous kinship relations and governance practices.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.473
Threshold uncertainty score0.940

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0110.017
Scholarly communication0.0050.003
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.013
GPT teacher head0.303
Teacher spread0.290 · 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

Citations46
Published2018
Admission routes2
Has abstractyes

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