The great divide between business schools research and business practice
Bibliographic record
Abstract
In their 2005 Harvard Business Review article, Bennis and O’Toole described business schools as being “on the wrong track” as a result of their focus on so-called scientific research. Some commentators argue that business schools have slowly lost their relevance since the end of the 1950s when they undertook a major overhaul in response to the harsh criticism of the Ford and the Carnegie Foundations on the state of theory and research in business administration. Inspired by Khurana’s (2007) book on the development of American business schools, this article describes the debate on the relevance of scientific business research that can be found in the popular business press and the academic literature, and suggests a number of structural and cultural changes to increase the relevance of business research and its impact on practice.
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 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 | 0.052 | 0.064 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.006 | 0.060 |
| Scholarly communication | 0.021 | 0.023 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 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".