Bibliographic record
Abstract
The chapter begins with an introduction to globalization and discusses its strengths and weaknesses in the context of capitalism. Authors make the case that the net present value of globalization has been positive for both economic growth and human well-being. Consequently, they argue that globalization may serve as a paradigmatic platform for business education. The chapter places emphasis on the Master of Business Administration (MBA) program, as it is generally understood that professionalization of management takes place at the MBA level. Authors offer a theory of business education that incorporates globalization as a permeating notion in generating a usable body of business knowledge that would serve as the basis for management training. They outline parameters of management training that identify critical skills that contribute to managerial competence. By combing the two and an integrated business education and managerial competence, globally relevant model is presented. Then, in the context of our model, we address the leadership role of Canadian business schools in promoting a globalized curriculum for business education and management training. The leadership focuses on academic, institutional, professional, and political roles that academic institutions and accreditation bodies might be called upon to play. The chapter concludes with some strategies for globalizing business education that Canadian business schools can implement.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".