Strategic Planning for Sustainability in Canadian Higher Education
Bibliographic record
Abstract
This paper reviews representations of sustainability in the strategic plans of Canadian higher education institutions (HEIs). A content analysis of the strategic plans of 50 HEIs was undertaken to determine the extent to which sustainability is included as a significant policy priority in the plans, including across the five domains of governance, education, campus operations, research, and community outreach. We found 41 strategic plans with some discussion of sustainability, and identified three characteristic types of response: (i) accommodative responses that include sustainability as one of many policy priorities and address only one or two sustainability domains; (ii) reformative responses that involve some alignment of policy priorities with sustainability values in at least a few domains; and (iii) progressive responses that make connections across four or five domains and offer a more detailed discussion of sustainability and sustainability-specific policies. Accommodative responses were dominant. More progressive responses were typically from institutions participating in the Sustainability Tracking, Assessment and Rating System (STARS) of the Association for the Advancement of Sustainability in Higher Education. The paper concludes with consideration of the political and economic contexts contributing to this relative prevalence of accommodative responses to sustainability.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.023 | 0.011 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".