Unexpected Succession: When Children Return to Take Over the Family Business
Bibliographic record
Abstract
This research explores family succession in which the successors were unexpected. We present six cases studies of children who initially pursued careers outside the family firm but who later decided to return and successfully take over the small family business. Our outcomes explain why they decided to return, the conditions that they set for succeeding their fathers, and the way they approached the management of the family firm. We show that the success they experienced in their professional careers far from the family business positioned them as legitimate leaders. They made a deliberate personal choice to succeed, negotiating the conditions, and this put them on the same level as their predecessors. These successors act as entrepreneurs, they are proactive, take risks, detect new business opportunities and do not hesitate to innovate. The changes that they implement are possible thanks to the support of their predecessors who avoids the destabilization of the organization.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".