The Best of Firms, the Worst of Firms: Ethical Bifurcation in Family Businesses During Crises
Bibliographic record
Abstract
Despite the ample progress being made in the study of family business ethicality, there remains a lack of consensus in the findings and some ambiguity concerning the concept. Building on a modified socioemotional wealth perspective, we theorize why family firms are likely to manifest both exceptionally ethical and equally unethical behavior during crises. We argue this to be caused by the close socioemotional connection between family owners and their firms, the decision-making discretion afforded these owners, and the secrecy and privacy with which they can act. We extend our framework to multiple stakeholders – employees, customers, and local, national, and global communities, and provide positive and negative examples as firms confront specific economic, human, and natural crises – demanding situations that reveal authentic ethicality when the pressure is on. We also introduce the notions of ethical heterogeneity, focus and coverage, and their moderators, arguing that the same family and firm may exhibit both ethical and unethical behavior depending on the crisis and stakeholders concerned. Propositions are provided throughout, and research implications are drawn.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.018 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".