Bibliographic record
Abstract
Economic activity is shaped by a large number of institutions and factors other than the prices set in markets. Among these institutions, familial and political relationships represent important nonmarket forces which impact economic decisions and firm strategies. In this paper, we study how social ties influence the organization and performance of firms in South Korea. Family firms are an important form of economic organization (La Porta et al., 1999; Allouche and Amann, 2000). In the United States, 35 % of the companies in the S&P 500 are substantially owned by families (Anderson and Reeb, 2003b), and family firms account for 40 % of U.S. GDP and 60 % of employment. Family firms are even more important in other economies, including Canada (Morck, Strangeland and Yeung, 2000), Western Europe (Faccio and Lang, 2002) and many countries in Asia (Claessens, Djankov and Lang (2002). In South Korea, as in most emerging economies, family firms are not just important but the ubiquitous form of business organization. It is exceptionally rare to find a Korean firm without one of the following characteristics: a founder-owner-manager, an heir-owner-manager, multiple family members with shared ownership under one family head, or multiple controlling
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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 | 0.005 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.550 | 0.263 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".