Bibliographic record
Abstract
Simon Fraser University, from the time of its opening in the 1960s, has striven to be a modernist and progressive educational institution. These characteristics are reflected in the architectural designs of its campuses, its epistemological orientations and offerings, and its policies. The university also states an ambition to be "Canada's most engaged university" on its website (sfu.ca/about.html). It is in considering this last point that this paper questions and considers SFU's 'engagement' in the context of the emerging environmental crisis. In particular, this paper focuses attention on the Burnaby Mountain campus and considers its place - geographically, architecturally, and culturally, and how these considerations of place intertwine and contribute or detract from a sense of engagement. Overall, this author posits that Simon Fraser's Burnaby Mountain campus is critically alienated from the in-situ forest that surrounds it, through character and gesture, and this is most unfortunate given a stated need by experts and educators to deepen engagement with natural environments in this time of crisis. Insights from place-based education identify that in-situ ecological knowledge, and insights arising from First Nations peoples, can help to grow new knowledge and awareness, deepen resiliency, and affect positive cultural change. The author suggests that Simon Fraser's Burnaby Mountain campus is an appropriate location to grow such a place-based education program and deepen its engagement in new, valuable ways.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".