Harley's Course -Integrating teachings from western and Indigenous sciences in an undergraduate biology course
Bibliographic record
Abstract
What is science? Whose knowledge do you value and why? Is there room for spirituality in science? These are core questions in the third-year biology course officially titled Common Ground: Learning from the Land (BIOL3201) offered at Mt Royal University (Calgary, Alberta, Canada). Commonly referred to as "Harley's Course", this course was co-developed with Piikani Knowledge Holder Harley Bastien. The purpose of the course is to expose students to comparative scientific perspectives-Indigenous perspectives based on relationships with creation and respect for the natural order of life, with western perspectives based on maximizing land productivity and management. It encourages students to challenge their beliefs about what science is, who is a scientist, what it means to 'think scientifically', how to listen and observe, and the validity of the immeasurable. The opportunity to experience relational land-based learning, and to have the flexibility and freedom to discuss and reflect on perspectives different from the dominant western perspective has a remarkable impact on the students. This paper includes lessons learned from the first three cohorts of students who participated in 'Harley's Course' and shares some of the challenges inherent in decolonizing the western post-secondary science curriculum.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.022 | 0.004 |
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".