Buoys & Anchors: Owning Family Behaviours that Influence Non-family Manager Preferences to Stay
Bibliographic record
Abstract
This paper addresses calls for greater attention to the non-family managers who work within family-owned firms. Expected to play increasingly prevalent and influential roles within such organizations in the future, we suggest that these employees will be especially sensitive to how owning-family members behave towards them because of their non-kin status. In keeping with this overarching argument, we theorize two family-member behaviors likely to influence a non-family manager’s desire to stay: (1) enacting practices on an ongoing basis that are consistent with fostering self-determined motivation; and, (2) enacting even a single yet emotionally charged encounter with unexpectedly positive or negative outcomes for the manager. The robust empirical findings obtained through our mixed- methods study support the hypothesized effects of these respective ‘buoys’ and ‘anchors’ net of alternative explanations; they also support the central premises underlying our theorizing. In addition to offering several contributions to and implications for the family business and organizational behaviour literatures, our work provides practical guidance for family firm leaders who are concerned about retaining their non-family managers. [N=170]
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".