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Record W4283788374 · doi:10.18584/iipj.2022.13.1.10700

Thematic Analysis of Indigenous Students’ Experiences with Indigenization at a Canadian Post-secondary Institution: Paradoxes, Potential, and Moving Forward Together

2022· article· en· W4283788374 on OpenAlexaffvenueabout
Iloradanon Efimoff

Bibliographic record

VenueInternational Indigenous Policy Journal · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsUniversity of ManitobaFirst Nations Health and Social Secretariat of Manitoba
Fundersnot available
KeywordsIndigenizationIndigenousStatus quoSociologyInstitutionPhenomenonThematic analysisPoolingRepresentation (politics)Political scienceSocial scienceEpistemologyAnthropologyQualitative researchLawComputer science

Abstract

fetched live from OpenAlex

Indigenization is a relatively new phenomenon in Canada. It is a broad concept that includes everything from changing physical spaces to challenging Western epistemologies and the status quo. In this study, I describe nine Indigenous students’ experiences with Indigenization at the University of Saskatchewan. Students were impacted both positively and negatively by their engagement: They described both opportunities borne of engagement with Indigenization and detriments such as exhaustion and lack of basic needs. In terms of methods to Indigenize, the participants described the importance of representation, centring Indigenous values and knowledges, and creating communities that can Indigenize. I end the paper with four policy recommendations for post-secondary institutions interested in Indigenization.

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)0.011
metaresearch head score (Gemma)0.011
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 score0.281
Threshold uncertainty score0.565

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.007
Science and technology studies0.0240.016
Scholarly communication0.0070.002
Open science0.0030.007
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.302
Teacher spread0.289 · 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

Citations4
Published2022
Admission routes3
Has abstractyes

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