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Record W2549444383 · doi:10.1163/1569206x-12341483

Hunting Theories: Totalisation and Indigenous Resistances in Canada

2016· article· en· W2549444383 on OpenAlexaffabout
Peter Kulchyski

Bibliographic record

VenueHistorical Materialism · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Economy and Marxism
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsIndigenousOpposition (politics)MaterialismResistance (ecology)SociologyArgument (complex analysis)White (mutation)Historical materialismGender studiesAestheticsEpistemologyPolitical scienceLawPoliticsMarxist philosophyPhilosophy

Abstract

fetched live from OpenAlex

Indigenous peoples are, in the current historical conjuncture, leading the opposition to the capitalist state in Canada. The specific features of Indigenous cultures, history and struggles demand of historical materialism a regional theory that deploys existing concepts and categories in reinvigorated and sometimes different ways. Glen Coulthard’s Red Skin, White Masks makes a critically important contribution to this project by offering a creative, materialist-leaning reading of Frantz Fanon as a lever to criticise those prominent liberal arguments of Indigenous conflict that are based on notions of recognition. While Coulthard’s argument and project would be significantly advanced by raising Marx’s concept of ‘mode of production’ from the secondary status it enjoys in the work to a more foundational role, in part because this moves the problem of totalisation to the core of strategies of resistance, he nevertheless in his affirmative project rightly centres returning to aboriginal cultural forms as a critical feature of decolonisation.

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 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)0.000
metaresearch head score (Gemma)0.000
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 score0.919
Threshold uncertainty score0.787

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.011
GPT teacher head0.216
Teacher spread0.205 · 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 teacher head, 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
Published2016
Admission routes2
Has abstractyes

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