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Record W7001115540

Indigenous Student-Led Decolonial Movements in Higher Education: A Case Study of the Indigenous Course Requirement at the University of Winnipeg

2023· report· en· W7001115540 on OpenAlexaboutno aff

Bibliographic record

VenueWinnSpace (University of Winnipeg) · 2023
Typereport
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousGraduation (instrument)Traditional knowledgeIndigenous educationColonialismHigher educationFocus group
DOInot available

Abstract

fetched live from OpenAlex

This research study seeks to explore the nature of decolonial tactics and strategies, theorized as decolonial movements, that are engaged by Indigenous students in higher education through a case-study of the Indigenous student-led initiatives that led to the mandatory ICR at UWinnipeg in 2016. The ICR at UWinnipeg was specifically chosen for this analysis as UWinnipeg was one of the first universities in Canada to implement an ICR for all undergraduate students as a graduation requirement, and the initiative was Indigenous student-led, as opposed to being driven by the university’s academic leadership. This study relies on one-to-one interviews with students that led these initiatives, and a focus group session with current Indigenous students to engage their narration of the ICR. This study seeks to identify and understand student-led movements that challenge colonial legacies in higher education institutions with attention to the significance of Indigenous histories, places, and knowledge systems.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.988
Threshold uncertainty score0.908

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.007
Scholarly communication0.0030.001
Open science0.0020.005
Research integrity0.0010.002
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 head0.063
GPT teacher head0.318
Teacher spread0.256 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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