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Record W4409215596 · doi:10.5430/bmr.v14n1p8

AACSB Accreditation – Fraud or Incompetence?

2025· article· en· W4409215596 on OpenAlexvenueno aff
Cam Caldwell, Verl Anderson

Bibliographic record

VenueBusiness and Management Research · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Marketing Education
Canadian institutionsnot available
Fundersnot available
KeywordsAccreditationBusinessAccountingLawPolitical science

Abstract

fetched live from OpenAlex

The Association for the Advancement of Collegiate Schools of Business (AACSB) was established in 1916 to be the guarantor and standard setter for ensuring the quality of business school education. In the decades that have followed this past century the needs of business students, employers, and business schools, and society have evolved and the criteria for accrediting business schools have been challenged. We review the evolving history of business education, the criticisms that has been made about the AACSB and its standards and identify concerns about the degree in which that accrediting body is fulfilling its original intended role. We suggest that the AACSB and business school administrators have failed to honor their moral obligation to business students, and future employers by decreasing their standards and failing to ensure that business school education is relevant to the needs of society.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.035
metaresearch head score (Gemma)0.160
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score0.187

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.160
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0050.021
Scholarly communication0.0120.010
Open science0.0020.006
Research integrity0.0110.011
Insufficient payload (model declined to judge)0.0070.003

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 head0.054
GPT teacher head0.352
Teacher spread0.297 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2025
Admission routes1
Has abstractyes

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