Finding balance in teaching Indigenous Studies and settler colonialism
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
eaching Indigenous histories has always been a journey for me.I am a non-Indigenous White settler-scholar who teaches Indigenous histories to primarily non-Indigenous students in a large, urban, multicultural university.I occupy a place of discomfort.I was drawn to this place of discomfort because I grew up in a small prairie town, where Indigenous and settler inhabitants grew up together, went to school and church together, worked together, and lived beside one another.Racism, cooperation, and compassion existed side by side.I wanted to understand the deep history of my town.My personal story on the land began at the turn of the 20th century when the Canadian government sponsored my Ukrainian great-grandparents to come to Manitoba to farm the land.I wanted to go deeper, to find out who occupied the land since time immemorial, and I was drawn to the histories of Mtis, Anishinaabe (Ojibwe), and Nehinaw (Cree).Over time, I got my PhD and found a job in the History Department at York University.I carved my academic life as an ally, researching the histories of colonial encounters in the fur trade and building courses about early
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.011 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it