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Record W6884638606 · doi:10.11575/cpai.v6i1.76517

Broken Circle: Exploring Indigenous Perspectives of Academic Integrity

2022· article· en· W6884638606 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Calgary · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicAcademic integrity and plagiarism
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousStewardship (theology)InstitutionAcademic integrityReciprocalIndigenous cultureStructural integrity

Abstract

fetched live from OpenAlex

Across the land now known as Canada, a growing body of research confirms the importance of academic integrity in higher education. Indigenous voices, though, are largely subsumed within the morass of dominant student and faculty perspectives or segregated alongside international student perspectives. Using the imagery of the Medicine Wheel as a framework, this session explores the views of Indigenous faculty, staff, administrators, and graduates affiliated with a mid-sized post-secondary institution in British Columbia. Findings from a small-scale research study reveal a holistic vision of academic integrity that emphasizes relationships with people and knowledge. As Wilson (2008) explains, “relationships do not merely shape reality, they are reality” (p.7). In this relational paradigm, academic integrity is inseparably grounded in the broader principles of integrity, and relies on reciprocal truth-telling to maintain the wholeness of the circle (Lindstrom, 2022). In this session, participants will gain insights into the ways dominant approaches to academic integrity can break the circle of integrity. The session will review similarities and differences between the experiences of Indigenous and non-Indigenous learners, and will consider how Indigenous views of relationality may foster a culture where stewardship of knowledge strengthens the bonds of integrity for all.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.257
Teacher spread0.221 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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