Odd couples: reconciling academic and operational cultures for whole-institution sustainability governance at universities
Bibliographic record
Abstract
Purpose This study aims to explore barriers and pathways to a whole-institution governance of sustainability within the working structures of universities. Design/methodology/approach This paper draws on multi-year interviews and hierarchical structure analysis of ten universities in Canada, the USA, Australia, Hong Kong, South Africa, Brazil, the UK and The Netherlands. The paper addresses existing literature that championed further integration between the two organizational sides of universities (academic and operations) and suggests approaches for better embedding sustainability into four primary domains of activity (education, research, campus operations and community engagement). Findings This research found that effective sustainability governance needs to recognise and reconcile distinct cultures, diverging accountability structures and contrasting manifestations of central-coordination and distributed-agency approaches characteristic of the university’s operational and academic activities. The positionality of actors appointed to lead institution-wide embedding influenced which domain received most attention. The paper concludes that a whole-institution approach would require significant tailoring and adjustments on both the operational and academic sides to be successful. Originality/value Based on a review of sustainability activities at ten universities around the world, this paper provides a detailed analysis of the governance implications of integrating sustainability into the four domains of university activity. It discusses how best to work across the operational/academic divide and suggests principles for adopting a whole institution approach 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 | 0.032 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".