Accountability, Relationality and Indigenous Epistemology: Advancing an Indigenous Perspective on Academic Integrity
Bibliographic record
Abstract
Abstract Although the notion of academic integrity is advanced as a Western construct, Indigenous ways of conceptualising and mobilizing this construct represent a vast, diverse and enduring knowledge system that encompasses not only how sources of knowledge are attributed, but also serves as one of the ontological pillars that upholds honesty and truth-telling within a relationally oriented epistemology. Written from an Indigenous perspective, this chapter invites readers to critically reflect on the ways that academic integrity, as an ethical pillar of the Western academy, relies on institutionalized protocols that privilege a specific methodology of citation and referencing that elevates the written word whilst excluding Indigenous methodologies that are embedded within an ethic of truth-telling and relational accountability. Grounded in the scholarship that surrounds Indigenous knowledge as a participatory way of knowing and utilizing a values-based analysis, I highlight the conceptual parallels between Western understandings of academic integrity and an Indigenous relational epistemology that is rooted in accountability. In today’s social climate of reconciliation, academic institutions across Canada are seeking avenues to decolonize their pedagogies and practices. One such avenue is in the area of academic integrity which is underlain with distinct and established ways of transmitting knowledge that have all too often left Indigenous knowledge systems to exist as alternative, or less rigorous, approaches to knowledge production. Movement towards a more equitable, critical and comprehensive understanding of how we, as scholars, are being accountable to those voices that inform and shape our own requires the consideration of a trans-systemic approach.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.031 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.018 | 0.092 |
| Scholarly communication | 0.018 | 0.019 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".