Settler Starting Points: Mapping a Model for Decolonising Practices in Higher Education
Bibliographic record
Abstract
Arising from a literature review and an autoethnographic, autobiographical narrative study, this theoretical-conceptual paper presents Settler Starting Points (SSP), developed for use by non-Indigenous, settler educators, in post-secondary education in Canada (and potentially beyond), who seek to decolonise and centre Indigenous Ways of Knowing, Being, Doing, and Relating in their teaching and curricular practices. Identifying key challenges and opportunities, the author maps possible trailheads to begin a journey of decolonising one’s own epistemology and ontology. Through a visual representation and textual description of the process model and a series of questions for critical self-reflection, SSP incorporates a holistic Indigenous framework - intellectual, spiritual, emotional, and physical dimensions - to present four starting point: humility (epistemic modesty), relationality (co-curriculum making), responsibility (authentic ally), and land (place-based attention).
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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.010 | 0.027 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".