University United : A review of the applied student research model in campus sustainability and its value for McGill
Bibliographic record
Abstract
This is an exciting time to be involved in the sustainability movement at McGill. In ouracademic offerings, the McGill School of Environment just celebrated its 10th anniversary,while on the administrative side, we have just opened the McGill Office of Sustainability,and the university is drafting its first set of Sustainability Principles. As well, the 2009edition of our annual Rethink conference will be the most ambitious yet. Working withprofessors and administrators, students are leading a significant and diverse set of projectsto improve our university - from Tapthirst empowering the university's public waterinfrastructure and Gorilla Composting installing McGill!s first industrial composting system,to Rethink Your Curriculum supporting the integration of sustainability across theuniversity!s curriculum. The campus is alive with collaborations between students,professors, administrators and community members, including the established success ofthe Edible Campus urban garden and the freshly inaugurated Farmers Market at McGill.
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 | 0.025 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.013 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".