Institutional Motivations for Conversion from Public Sector Unit to a Social Business: The Case Study of Burgundy School of Business in France
Bibliographic record
Abstract
Based on a qualitative single case study with eight interviews, this study lays the foundation for literature on the motivation for transforming from a quasi-governmental entity to a social business. The context of this case study is a spin off of business schools from the French chambers of commerce and industry. This spin off was encouraged by enabling legislation that allowed assets specific to business schools to be transferred without taxes and fees if they adopted this legal business form. This case study is on the Burgundy School of Business, one of the seven schools that have adopted the regime. The school is also a member of the Principles of Responsible Management in Education. This case study suggests that the motivation for adopting a social business form could be institutional rather than personal. International rankings influence country legislation and business form adoption in a competitive industry. This case also discusses why the school has intentionally decided not to go for a digital transformation of its core business model. This case leads to theoretical propositions that consider the conditions under which public sector enterprises may spin off units as social businesses focused on their beneficiaries, and the control mechanisms that need to be instituted by the parent enterprise.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.009 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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".