Principles for Responsible Management Education: An Axiological Approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this article, we rely on the development of a Massive Open Online Course (MOOC) to show the relevance of a values-based approach to responsible management. To clarify the notion of values, we draw on Heinich’s axiological sociology, which presents values as principles of judgment and action. Building on this approach, we interviewed 35 management scholars to understand the values they attribute to responsible management. Our analysis led to the identification of seven actionable values that can be used to circumscribe responsible management. We also show how three interrelated levels of analysis—namely, individual (micro), organizational (meso), and societal (macro)—allowed us to further organize the interview data to produce rich content for the MOOC. Our contribution is twofold: first, our values-based approach helps overcome the axiological ambiguity of the Principles for Responsible Management Education (PRME), which invoke the importance of incorporating “the values of global social responsibility” (Principle 2), but fail to define and operationalize these values. Second, we provide a rationale and guidance for implementing values-based responsible management education in Business Schools.
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.
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 | 0.010 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it