Sustainability Policies if Necessary but Not Necessarily Sustainability Policies
Bibliographic record
Abstract
The paper examines the appropriateness and limitations of campus sustainability policies as a tool for advancing campus sustainability. It begins by exploring the case of a mid-sized university in the prairie region of Canada, the University of Regina, along with the co-evolution of the Regional Centre of Expertise on Education for Sustainable Development in Saskatchewan (RCE Saskatchewan), of which the University of Regina is a founding partner. It highlights the challenges implementing sustainability policies in both contexts yet, despite this absence of policy, the respective advances in campus sustainability initiatives through each. To account for this seeming paradox, the paper explores how, while on the surface, sustainability policies might be viewed as central to advancing specific social and political sustainability objectives within an organization along with greater efficiency and effectiveness in resource allocation towards sustainability goals, the nature of policy within an increasingly corporatized university structure and professionalized sustainability management system may potentially impede these objectives. The paper concludes by highlighting the value of a decentralized approach that respects and integrates the traditional scholarly accountability of universities that promote academic freedom along with a current need to create sustainable scholarly livelihoods that advance this freedom in an increasingly restrictive organizational environment.
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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 | 0.018 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.018 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 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".