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Cautionary Stories of University Indigenization: Institutional Dynamics, Accountability Struggles, and Resilient Settler Colonial Power

2020· article· en· W3137873483 on OpenAlexaboutno aff
Erich Steinman, Scott Scoggins

Bibliographic record

VenueAmerican Indian Culture and Research Journal · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenizationAccountabilityIndigenousDecolonizationSociologyColonialismHigher educationPolitical scienceAutonomyPower (physics)InstitutionPower structureSocial scienceLawAnthropologyPolitics

Abstract

fetched live from OpenAlex

Increasingly, a discourse of indigenizing is being articulated in United States higher education. This article contributes to the limited existing research that examines how indigenization processes, well underway in Canada, are able to transform post-secondary institutions and/or how transformation is resisted and contained. With attention to institutional dynamics, Native studies’ centering of community accountability, and patterns of settler-colonial power, the study centers the perspectives and experiences at one university of Indigenous students, faculty, staff, and community partners. Interviews reveal four tensions or challenges of indigenization. “Hidden contributions” are the result of Indigenous people bearing the burden of rectifying the institution’s default colonial practices. Many individuals attempt to satisfy a challenging “dual accountability” to both First Nations and the university. Contradictions and uneven advances across the university create starkly varying experiences and reveal both promising change and disappointment. Finally, participants envision going beyond indigenization and decolonization by centering Indigenous intellectual autonomy and increasing accountability to First Nations. Interpreting these experiences and perceptions through logics of inclusion, reconciliation, and decolonization, the study suggests strategic approaches to address these tensions in future efforts in Canada and the United States.

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 score0.251
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.032
GPT teacher head0.337
Teacher spread0.305 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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