Sustainability in Canadian post-secondary institutions
Bibliographic record
Abstract
Purpose – This paper aims to report on a census of high-level sustainability initiatives at all accredited post-secondary institutions in Canada by documenting the institutions that have undertaken sustainability assessments, have signed one or more sustainability declarations, have sustainability offices or officers or have sustainability policies. The aim was to better understand the broad-scale patterns of commitments by post-secondary institutions to these sustainability initiatives by exploring the interrelationships among them, and with geographic and institutional characteristics. Design/methodology/approach – Data were collected on existing high-level sustainability initiatives at Canada’s 220 accredited post-secondary institutions. Patterns in the data were analyzed using exploratory statistical techniques. This paper proposes a sustainability initiative score to help understand the diversity and patterns of sustainability initiative uptake. Findings – Institutions located in larger communities, and in British Columbia and Québec, tended to have higher sustainability initiative scores. Institutions in Saskatchewan and the territories had the lowest sustainability initiative scores. It was found that sustainability office(r)s, assessments and policies co-occurred disproportionately, potentially suggesting positive reinforcement mechanisms. On the other hand, having signed a declaration was not strongly linked to other sustainability initiatives. Terminological preference had shifted from “environment” and “sustainable development” to “sustainability”. Research limitations/implications – The scope was limited to a discrete set of high-level sustainability initiatives appropriate for a nation-wide census, at a moment in time, and is therefore not exhaustive in subject or temporal extent. This broad-scale comparative analysis compels further study into the relationship between the sustainability policy environment and sustainability practices on the ground, as well as implications for how post-secondary institutions engage with sustainability. The patterns and interrelationships this paper discovered help to structure future critical and comparative in-depth analyses of sustainability policies and practices within post-secondary education. Originality/value – Almost no extensive, comparative empirical studies of sustainability policy and practice in post-secondary institutions exist. This void is addressed by documenting and analyzing high-level sustainability initiatives across all accredited post-secondary institutions in Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".