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Record W4399391113 · doi:10.1177/23996544241259361

Decolonizing blockades: Settler-citizen solidarities with Indigenous blockades

2024· article· en· W4399391113 on OpenAlexaffabout
Peter Nyers

Bibliographic record

VenueEnvironment and Planning C Politics and Space · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicAnthropological Studies and Insights
Canadian institutionsMcMaster University
Fundersnot available
KeywordsIndigenousPolitical scienceBiologyEcology

Abstract

fetched live from OpenAlex

In the Winter 2020, Canada witnessed an extraordinary number of blockades and solidarity protests in support of the Wet’suwet’en First Nation. The Wet’suwet’en had for years been fighting against the construction of an oil pipeline across their traditional territories. After a police raid dismantled their blockade, the traditional chiefs of the Wet’suwet’en issued a call for solidarity and support. The response was overwhelming with an enormous number of solidarity actions, including blockades of critical infrastructure, organized across Canada and internationally. This paper critically examines how settler-citizens engaged in acts of solidarity with Indigenous people, with a particular focus on how these acts of solidarity can contribute to the decolonization of Canadian citizenship. Since the Wet’suwet’en struggle involved the assertion of Indigenous sovereignty, the solidarity actions of Canadians raise important questions about the meaning of settler forms of citizenship. This paper takes a relational and decolonial perspective on solidarity blockades. Such an approach allows us to ask questions that are outside the scope of assessments concerned with the efficacy of a particular blockading action. The paper investigates the forms of solidarity found at the blockades, noting that a wide range of antagonistic, agonistic, and spatio-temporal relations were enacted at the various blockading actions. These relations allowed for a contentious production of new political subjectivities, collectivities, and citizenships.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.879
Threshold uncertainty score1.000

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 studies0.0010.001
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 head0.019
GPT teacher head0.274
Teacher spread0.255 · 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 designNot applicable
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

Citations1
Published2024
Admission routes2
Has abstractyes

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