Integrating Sustainability in Management Education
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
Over the last decade, numerous modules, courses, and programs in Management Education have integrated sustainability into their curricula. However, this “integration” has translated into very diverse forms and contents. This article aims to clarify these ambiguities. It maps four forms of sustainability integration in Management Education. These four distinct forms are (1) discipline-based integration, in which the anchoring point is the business discipline (sustainability is added as a dimension of this body of knowledge); (2) strategic-/competitive-based integration, in which the anchoring point is the strategy of the organization (sustainability is viewed as a potential contributor to the firm’s competitive advantage); (3) integration by application, in which managerial tools and approaches from business disciplines are applied so as to contribute to addressing a sustainability challenge; and, last, (4) systemic integration, in which the anchoring point is a social-ecological-economic challenge defined from an interdisciplinary perspective. Implications of this chapter for the design of courses and programs and the practice of sustainability in Management Education are twofold. First, this article contributes to going beyond the prevailing tendency of studies in the field of sustainability in Management Education to focus mainly on tools and applications. In doing so, this article helps frame these challenges on the level of course and program design. Second, this article helps management educators map what they are intending to achieve by the integration of sustainability into the Management Education curriculum.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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 it