Mapping social structures for sustainability transformation at McGill University, Canada
Bibliographic record
Abstract
Purpose For a university to be a prime mover for sustainability transformation, all units of the university should contribute. However, organizational change in educational institutions is often studied by examining specific domains such as research or operation in isolation. This results in a less-than-complete picture of the potential for university-wide change. In contrast, this paper aims to examine the network of social relations that determine the diffusion and sustainability of change efforts across a university. The authors use McGill University (Canada) as a model system to study the network of actors concerned with sustainability to learn how this network influences the penetration of sustainability throughout the university. Design/methodology/approach To explore the existing social structure, the authors use an innovative approach to illuminate the influence of social structure on organizational change efforts. Using a mixed methods approach combining social network analysis with qualitative interview data, the authors examine the influence of the social structure on sustainability transformation at McGill University. The authors conducted 52 interviews between January and April 2019 with representatives of different sustainability groups at the university across six domains (research, education, administration, operations, connectivity and students). Findings The authors find that McGill University has a centralized system with a low density. The network is centralized around the Office of Sustainability. The limited cross-domain interaction appears to be a result of differences in motivation and priorities. This leads to a network that has many actors but only a limited number of connections between them. The quality of the relationships is often utilitarian, with only a few relationships aiming for support and mutual growth. Originality/value This study brings together social network analysis, sustainability transformation and higher education in a new way. It also illustrates the complexity of guiding a large organization, such as a university, toward a sustainability transformation. Furthermore, it reveals the importance of considering each part of the university as part of an interconnected network rather than as isolated components.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".