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Record W2071911146 · doi:10.1080/2201473x.2013.810694

Troubling good intentions

2013· article· en· W2071911146 on OpenAlexaff
Sarah de Leeuw, Margo Greenwood, Nicole Lindsay

Bibliographic record

VenueSettler Colonial Studies · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicCritical Race Theory in Education
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsIndigenousColonialismDominance (genetics)SociologyDiversity (politics)Environmental ethicsPolitical sciencePolitical economyGender studiesLawAnthropologyEcology

Abstract

fetched live from OpenAlex

We are unequivocally in favor of much, much, more space opening up for Aboriginal peoples and Indigenous ways of knowing and being in academic (and myriad other) spaces. We are worried, however, about a current lack of published critical engagement with policies and practices that appear, superficially, to support inclusivity and diversity of Indigenous peoples in academic institutions. We argue that, principally because such policies are inherently designed to serve settler-colonial subjects and powers, many inclusivity and diversity policies instead leave fundamentally unchanged an ongoing colonial relationship with Indigenous peoples, their epistemologies, and their ontologies. Indeed, we contend that individual Aboriginal peoples are suffering at deeply embodied levels as universities and other institutions rush to demonstrate well-intended “decolonizing” agendas. Drawing from examples in British Columbia, this paper provides a critical intervention into a rapidly ascending, and deeply institutionalized, dominance of policies and practices that claim to promote and open spaces for Indigenous peoples and perspectives within academic institutions. We draw from critical race theorists, including Sara Ahmed, and in our conclusion offer suggestions that aim to destabilize and trouble the good intentions of neo-colonial policies.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
gptno category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
models agreeAgreement compares identical category sets and study designs across arms.

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)0.028
metaresearch head score (Gemma)0.049
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.049
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0190.070
Scholarly communication0.0110.010
Open science0.0020.010
Research integrity0.0100.021
Insufficient payload (model declined to judge)0.0070.001

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 head0.059
GPT teacher head0.420
Teacher spread0.362 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical · Commentary

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

Citations53
Published2013
Admission routes1
Has abstractyes

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