Transforming the Business School Ethos Through the Teaching of a “Strong” Social Innovation: Pedagogical Opportunities and Tensions
Bibliographic record
Abstract
Over the past 15 years, social innovation (SI) has gained ground as a promising approach for tackling today’s grand challenges. A “weak” conception of SI focuses on improving how social needs are addressed through new products, services, technologies, business models, or practices. In contrast, a “strong” conception emphasizes deep social transformation and the empowerment of historically marginalized groups. In management education, SI has predominantly been taught through the lens of the weak conception. This paper explores the pedagogical opportunities and challenges of teaching a strong SI to business school students. We conducted a qualitative study of six courses that emphasize a strong SI, drawing on semi-structured interviews with both instructors and students. Our findings reveal the transformative potential of these courses, suggesting they can better prepare students to tackle today’s complex challenges by reshaping the traditional ethos of business schools. However, teaching a strong SI also requires instructors to navigate several key tensions related to action, organizations, management, emotional engagement with the world, and consideration of values and politics. These tensions offer a pedagogical map not only for courses centered on a strong SI but also for those adopting a critical approach to management and business organizations.
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 | 0.001 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".