Bibliographic record
Abstract
Climate change and social unrest are signs that the planet, and everyone on it, is at risk. Business schools have a responsibility to build and share knowledge to mitigate this crisis. One important step is to help students learn how to act in a sustainable manner—to ensure the prosperity of not just today’s generations, but also tomorrow’s, within planetary boundaries/limits. While some students are eager to learn about how to achieve sustainability, others push back against the idea of straying from a strict profit motive in business. In an interview with Dr. Pratima (Tima) Bansal, a highly accomplished sustainability scholar, she offers her own experiences on the challenges she has faced in the classroom and her approaches to increase teaching effectiveness. She covers several topics, including the often-divisive nature of sustainability; the power of encouraging systems thinking, a process ontology, and a focus on a desirable future; and advice for new faculty to approach work as art. Overall, the insights of Dr. Bansal may help other instructors to effectively prepare students to contribute to a more prosperous and sustainable future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".