Envisioning SoTL Through a Lens of Indigenous Cultural Continuity
Bibliographic record
Abstract
This paper is a renditioning of a closing keynote presentation I delivered at the 2022 Symposium for the Scholarship of Teaching and Learning – A Decade of Imagining SoTL: Looking Back, Looking Ahead hosted by the Mokakiks Centre for SoTL with Mount Royal University, Calgary, Alberta, Canada. The presentation highlighted how as SoTL researchers and educators, we are engaged in a deep relationship with knowledge - with our own knowledge and that of our students. These characteristics of SoTL hold parallels with Indigenous pedagogies, ways of knowing and the embodiment of knowing. This keynote brought possibilities to the fore through an Indigenous lens that sees knowledge generation as a site of continuous transformation. Through a critical discussion of key principles of an Indigenous paradigm, and illuminating that which is not taught, we might construct a praxis-based vision of SoTL that centers equity and relational accountability.
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 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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.070 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".