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Record W2966948751 · doi:10.1080/14443058.2019.1650797

Advocating Dialogue or Monological Advocacy? Settler Colonial Theory, Critical Whiteness Studies and the Authentic “Pro-Indigenous” Position

2019· article· en· W2966948751 on OpenAlexaboutno aff
Michelle Carey

Bibliographic record

VenueJournal of Australian Studies · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousScholarshipDecolonizationColonialismSociologyIdeologyGender studiesPoliticsCritical race theoryAestheticsRacismPolitical scienceLaw

Abstract

fetched live from OpenAlex

This article problematises settler colonial theory and critical whiteness studies and their role in supporting advocacy scholarship, or scholarship purporting to uphold Indigenous political aspirations. It examines the conceptual reliance of these paradigms on binarised, orthodox representations of Indigeneity and the role of these representations in supporting particular “pro-Indigenous” political priorities, such as decolonisation. By way of example, a retrospective engagement with Sarah Maddison’s Beyond White Guilt: The Real Challenge for Black–White Relations in Australia is offered. I argue that this text’s representation of all non-Indigenous people as “white” and “guilty” perpetrators constructs Indigenous people as “black” and (by implication) “innocent” victims. The circumscription of Indigeneity delimits the terms by which Indigenous people can articulate their interests in the dialogue proffered as evidence of decolonisation, thus rendering the dialogue a monologue. Underscoring the power of this monologue, a Métis critique of Indigenous cultural-nationalist anti-colonial movements is called upon to argue that those who employ orthodox representations of Indigeneity put their commitment to an ideological position above a negotiation of alternatives. Consequently, the task of theorising decolonisation is diminished, and those we seek to support in our scholarship remain marginalised in our representations of them.

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)0.004
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 score0.076
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0040.002
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 head0.055
GPT teacher head0.395
Teacher spread0.340 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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