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Record W4386819018 · doi:10.1002/sd.2757

Unlocking the potential of responsible management education through interdisciplinary approaches

2023· article· en· W4386819018 on OpenAlexaff
Flávio Pinheiro Martins, Luciana Oranges Cezarino, Lara Bartocci Liboni, Trevor Hunter, André Cavalcante da Silva Batalhão, Marco Antônio Catussi Paschoalotto

Bibliographic record

VenueSustainable Development · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSustainability in Higher Education
Canadian institutionsThe King's UniversityWestern University
Fundersnot available
KeywordsEngineering ethicsSustainabilityEducation for sustainable developmentSociologyManagement theoryKnowledge managementSustainable developmentManagement sciencePolitical scienceComputer scienceEngineering

Abstract

fetched live from OpenAlex

Abstract Business schools are crucial to integrating sustainable development into management thought and practices, thereby promoting a paradigm shift toward responsible management education. Despite many business schools pledging to adopt the United Nations' Principles for Responsible Management Education, they have been criticized for failing to develop change agents toward sustainability. To fill this gap, this paper demonstrates how interdisciplinarity can be connected to responsible management education through critical and instrumental perspectives. To this end, we apply an interdisciplinarity model to 37 Principles for Responsible Management Education Schools' Reports, using content analysis, text‐mining, and network theory tools. As a result, our findings suggest: (i) a taxonomy of critical and instrumental interdisciplinary studies and (ii) a framework of Principles for Responsible Management Education schools engaged in critical and instrumental interdisciplinarity. The framework we develop can serve as a diagnostic and prognostic tool for assessing how interdisciplinary can improve responsible management education in business schools. Our findings contribute to theory advancing research on the intersection of responsible management education and interdisciplinary approaches.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.403
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.036
GPT teacher head0.345
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations17
Published2023
Admission routes1
Has abstractyes

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