The Transacting Cognitions of Nonfamily Employees in the Family Businesses Setting
Bibliographic record
Abstract
Little previous research has focused on the perspective of nonfamily employees working in family owned businesses—this is remarkable considering that an estimated 80% of family business employees are not family members. In addition, the interaction of family and business systems in family businesses increases the cognitive expectations of nonfamily employees. Cognition is defined as all processes by which sensory input is transformed, reduced, elaborated, stored, recovered, and used. In order to succeed in these businesses, nonfamily employees must be able to understand and navigate both the company's family and business goals using complex cognitions. It is for this reason that understanding the cognitive complexity experienced by nonfamily members in family run firms is essential. Mitchell and Morse's transaction cognition theory is used to determine the transaction cognitions that accompany successful relationships between family and nonfamily employees in family businesses. The theory developed predicts seven cognitions that the nonfamily employee working in a family business must master in addition to mastering the knowledge (planning, promise, and competition cognitions) necessary for transacting in business in general. These include: (1) family productions planning cognitions, (2) family stakeholders planning cognitions, (3) family performances planning cognitions, (4) family promise cognitions, (5) family alignment cognitions, (6) self-interest cognitions, and (7) work proportion cognitions. (SFL)
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".