Bibliographic record
Abstract
This essay relates the experience and reflects on the impacts of the COVID-19 pandemic onstudents and myself(their instructor) as we muddled, plowed, stumbled, stalled, and occasionally sailed our way through Queering Indigenous Land-Based Education, a required course for students in the University of Saskatchewan’s Master of Education program with an Indigenous Land-Based Education concentration. Ordinarily, the course is presented as a land-based intensive, hosted by an Indigenous Nation. Students and faculty live on-site during the intensives, a context in which they can develop and deepen their relationshipswith their peers and instructors, and with their most valuable teachers, their Indigenous hosts and the land. This year, the COVID-19 pandemic forced our teaching off the land and into the digital realm. In consultation with other community-based and land-based educators and students, we reconstructed the course’s pedagogy and curriculum. This article shares what did and what did not work well in our reconstructed course, and reflects on how what we learned from this experience might inform future pedagogy and practice.
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 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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".