Perceptions About the Extent of Succession Planning in Canadian Family Firms
Bibliographic record
Abstract
Abstract Despite exhortations about the importance of succession planning for the family firm, many believe that family firms continue to leave succession planning to chance. This study shows that family members have different opinions about whether their family firms engaged in succession planning. The incumbents believe that they did while the other family members, including the successors, believe that they did not. We also present results showing that two factors with which the family business succession literature is most concerned—an incumbent ready to step aside and the presence of a competent successor—may influence the extent to which the Canadian family firm engages in succession planning. Résumé Malgré les consignes concernant l'importance de plani‐fier la succession d'une compagnie familiale, beaucoup d'entre nous croient que ces m4iCme famille different d'opinion a savoir si la compagnie s'est, oui ou non, engagée dans un processus de planification de la succession. Ceux et celles en place croient qu'ils l'ont fait quand les autres membres de lafamilee, incluant les suc‐cesseurs, croient le contraire. Nous presentons aussi des donnees qui démontrent que les deuxfacteurs qui préoc‐cupent la litérature dans le domaine—une personne en place prete a céder sa place et la presence d'un suc‐cesseur compétent—peuvent influencer le degré d'engagement de la compagnie familiale canadienne au processus de planification de la succession.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".