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Record W3081089963 · doi:10.1080/2201473x.2020.1807877

Unsettling as agency: unsettling settler colonialism where you are

2020· article· en· W3081089963 on OpenAlexaboutno aff
Erich Steinman

Bibliographic record

VenueSettler Colonial Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsColonialismScholarshipIndigenousRedressAgency (philosophy)SociologySolidarityContext (archaeology)Gender studiesEnvironmental ethicsPolitical scienceLawPoliticsSocial scienceHistory

Abstract

fetched live from OpenAlex

A great deal of recent sociological scholarship in Canada has examined the ‘unsettling' process motivating non-Natives or ‘settlers' to act in solidarity with Indigenous movements and their experiences of becoming unsettled through such engagements. Informed by settler colonialism and Indigenous studies concerns, such conceptualizations of unsettling have focused primarily on individual trajectories', in conjunction with an overriding normative emphasis on settlers’ active support for, and accountability to, Indigenous leadership.While invaluable, these predominating conerns leave open questions about the scope of appropriate agency for non-Native people in challenging settler colonialism. Scholarship to date lacks an explicit affirmative model for settlers to interrupt the routine institutional reproduction of settler colonial understandings, discourses and practices, which also limits its applicability to the United States context. Drawing upon sociological concerns with the institutional and organizational reproduction of power, the article discusses and disentangles differing notions of unsettling and suggests that, under larger covering norms of following Indigenous leadership and relationality, settlers can actively destabilize the reproduction of settler colonial reality through a disruptive form of quotidian agency wherever they are.

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)0.006
metaresearch head score (Gemma)0.008
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 score0.039
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0220.058
Scholarly communication0.0120.007
Open science0.0010.012
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0030.000

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 head0.046
GPT teacher head0.344
Teacher spread0.297 · 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

Citations34
Published2020
Admission routes1
Has abstractyes

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