Environment, not social or governance, oh my: sustainability priorities in Canadian university sustainability documents
Bibliographic record
Abstract
Purpose Universities are significant in their sustainability action not just for the education that they provide, but how they operate as mini cities, with massive environmental footprints, meaning that, their sustainability direction matters. As a result, this study aims to investigate the priorities present in university sustainability policy documents from 33 Canadian universities. Design/methodology/approach Comparing sustainability policies with the overarching goals of the United Nations sustainable development goals through the approach of narrative policy analysis, this research explores the priorities present and what patterns emerge in these priorities. Findings Findings include that across Canada, planet-related sustainability priorities, particularly those focused on cities, climate action and consumption, are the most present, while people and prosperity elements of sustainability often fall outside the scope of these policies. Some regional variation emerges in key areas such as energy and climate action, and size also sees a correlation to prioritization of specific areas of sustainability such as waste. Originality/value This research will be of interest to researchers in the emerging field of sustainability in higher education, practitioners and administrators in university sustainability and policymakers looking to understand sustainability prioritization shape the future of nuanced sustainability directions.
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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.013 |
| Science and technology studies | 0.026 | 0.011 |
| Scholarly communication | 0.015 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".