Post-pandemic responsible management education: an invitation for a conceptual and practice renewal and for a narrative change
Bibliographic record
Abstract
Purpose This essay makes the point that the corona crisis should motivate business schools and scholars to reflect on their interpretation of responsible management education (RME). It suggests both a conceptual and a practice renewal of RME, by respectively highlighting the relevance of the constructs organizational climate (OC) and professorial roles (PR) and calling for an enactment of business schools’ employer responsibility. It also argues that beyond mere techno-pedagogical and strategic developments, business schools’ post-pandemic challenges should encompass a narrative change. Design/methodology/approach Review of recent studies on the neo-liberalization of business schools and the implications of the latter on management educators and management education. Findings The corona crisis carries the risk of putting center stage and amplifying the entrepreneurial narrative in business schools. Such a narrative is deeply rooted in neoliberal assumptions. However, the corona crisis is also an opportunity to renew RME and to favour critical studies, encourage moral imagination and embark collectively on systemic activism. Originality/value Like other recent work, this paper reflects on what RME should mean and how business schools should set and fulfill their RME agenda in the aftermath of the corona crisis. To complement those former work, this paper proposes that the constructs of OC and PR be invited into the conceptualization of RME and insists that business schools acknowledge their employer responsibility.
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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 | 0.033 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.046 |
| Scholarly communication | 0.015 | 0.030 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.010 | 0.019 |
| Insufficient payload (model declined to judge) | 0.004 | 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".