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Record W3080836011 · doi:10.1080/02660830.2020.1807891

Learning towards decolonising relationships at standing rock

2020· article· en· W3080836011 on OpenAlexaffabout
Jenalee Kluttz, Judith Walker, Pierre Walter

Bibliographic record

VenueStudies in the Education of Adults · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIndigenousOpposition (politics)Reciprocity (cultural anthropology)Resistance (ecology)SociologyColonialismPolitical scienceLawSocial scienceEcologyPolitics

Abstract

fetched live from OpenAlex

The opposition to the Dakota Access Pipeline that took place at Standing Rock in North Dakota was the largest gathering of Indigenous Peoples in recent U.S. history. Thousands of people, Indigenous and otherwise, came together from across North America and beyond to protect waters and sacred sites threatened by the construction of the Dakota Access oil pipeline. Our study examined the learning of Canada-based pipeline activists who travelled to Standing Rock to support the opposition. In this paper, we argue that participating in the Standing Rock resistance camp was an experience rich in informal learning and education for both Indigenous and non-Indigenous participants, and that this learning might be best understood as learning towards decolonising relationships. Building from the theoretical concepts of respect, responsibility, reciprocity, and relationship as the overarching umbrella, we outline three types of relationships central to how Standing Rock activists learned within the resistance camp: relationships to people, to community, and to self. A focus on these relationships – and the centrality of respect, responsibility, and reciprocity to them – provides insight into how the resistance community created opportunities for participants to start to unlearn settler-colonialism, and learn towards a decolonising relationality.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.167
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
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 head0.087
GPT teacher head0.388
Teacher spread0.301 · 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.

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

Citations3
Published2020
Admission routes2
Has abstractyes

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