More green thoughts than actions: Insights from marketing instructors at a Canadian University
Bibliographic record
Abstract
Sustainability discourse provides directions for sustainable development in the global context; education should be transformed to address sustainability concerns. Many universities have adopted a sustainability focus and university instructors play a vital role in inculcating sustainability principles in students, but in business education there is little research on how marketing instructors interpret sustainability or how that affects their teaching. This qualitative case study used semi-structured interviews and content analysis of course syllabi to gain the insights of marketing instructors at a university in Canada; specifically, how they interpret sustainability, how they integrate sustainability into their marketing instruction, and the perceived factors affecting their teaching practices. Thematic analysis with NVivo identified a dilemma; business worldviews limit what marketing instructors think about sustainability and whether and how they teach it in marketing courses. If marketing instructors are not teaching about sustainability, it is a missed opportunity to transform production, consumerism and marketing. As universities are increasingly trying to implement sustainability integration in teaching and learning, this research provides useful implications for marketing instructors, educational leaders, business schools, professional associations and textbook publishers. • This case study explores marketing instructors' views on sustainability. • Business worldviews limit their practices of sustainability integration. • Aspirations for integrating sustainability exceed the practice. • External and internal barriers impede efforts for sustainability integration. • A supportive culture can lead to rapid progress of sustainability integration.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.038 | 0.016 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".