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Record W1480663984

Re-envisioning resurgence: Indigenous pathways to decolonization and sustainable self-determination

2012· article· en· W1480663984 on OpenAlexaff
Jeff Corntassel

Bibliographic record

VenueUVic’s Research and Learning Repository (University of Victoria) · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsDecolonizationIndigenousOperationalizationIndigenous rightsColonialismSelf-determinationPolitical scienceEnvironmental ethicsSociologyPoliticsGender studiesLawEcologyEpistemology
DOInot available

Abstract

fetched live from OpenAlex

Amidst ongoing, contemporary colonialism, this article explores Indigenous pathways to decolonization and resurgence with an emphasis on identifying everyday practices of renewal and responsibility within native communities today. How are decolonization and resurgence interrelated in struggles for Indigenous freedom? By drawing on several comparative examples of resurgence from Cherokees in Kituwah, Lekwungen protection of camas, the Nishnaabekwewag “Water Walkers” movement, and Kanaka Maoli (Native Hawaiian) revitalization of kalo, this article provides some insights into contemporary decolonization movements. The politics of distraction is operationalized here as a potential threat to Indigenous homelands, cultures and communities, and the harmful aspects of the rights discourse, reconciliation, and resource extraction are identified, discussed, and countered with Indigenous approaches centered on responsibilities, resurgence and relationships. Overall, findings from this research offer theoretical and applied understandings for regenerating Indigenous nationhood and restoring sustainable relationships with Indigenous homelands.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.968
Threshold uncertainty score0.064

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 studies0.0100.041
Scholarly communication0.0080.007
Open science0.0010.011
Research integrity0.0010.003
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 head0.020
GPT teacher head0.299
Teacher spread0.279 · 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

Citations454
Published2012
Admission routes1
Has abstractyes

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