Beyond the Name: Analysis of Cohesion Factor in Name Congruence and Socioemotional Wealth Relation of Family Business
Bibliographic record
Abstract
In the forthcoming study, our overarching objective is to embark on a comprehensive exploration of the intricate linkages between the family name and the socioemotional wealth intrinsic to family businesses. This investigation places a specific emphasis on unraveling the mediating role played by family cohesion in shaping these complex dynamics. Our theoretical endeavor seeks to make a distinctive contribution to the scholarly landscape by providing nuanced insights into the multifaceted relationships within family businesses. By anchoring our study in the foundation of established literature, our aim extends beyond expanding empirical understanding to substantively contribute to the theoretical discourse that shapes the broader landscape of family business dynamics. As we delve into this exploration, we anticipate our findings will not only enrich our understanding of the interplay between family names, family cohesion, and socioemotional wealth but also offer valuable insights for practitioners, policymakers, and scholars invested in the success and resilience of family-owned enterprises.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".