Education for sustainable development: an assessment of Australian and Canadian business schools
Bibliographic record
Abstract
Purpose This study aims to investigate whether and how business schools in Australia and Canada advocate for education for sustainable development. Design/methodology/approach This exploratory study used a sequential mixed methods design, using a combination of qualitative content analysis and thematic analysis. During phase 1, sustainability reports developed by Australian and Canadian business schools (SIP reports), which are signatories to the Principles for Responsible Management Education (PRME), were reviewed using qualitative content analysis methods. Following that, a thematic analysis of semi-structured interviews with nine representatives from selected business schools from Australia and Canada were conducted to triangulate and interpret the findings from phase 1. Findings Australian and Canadian business schools incorporate sustainability into their teaching practices through mandatory courses designed around sustainability and its relationship with business and linking sustainability with other business-related courses by including relevant aspects of sustainability with course contents. Sustainability education in Australia and Canada is being addressed through a variety of degree and non-degree programs showing an increasing relevance for sustainability across business schools. However, results also show differences between the two countries, dependence on leadership, at times lack of support and infrastructure and not always clear strategies to place sustainability at the core of business education. Originality/value Despite previous attempts at examining sustainability practices across business schools, there is a dearth of research looking into a cross-country comparison of integrating sustainability in learning and teaching for business education.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.016 |
| Science and technology studies | 0.012 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".