Grabbing Hands and Helping Hands: The Role of Concentrated Ownership during Crisis
Bibliographic record
Abstract
Using meta-analytic techniques on data from 70 primary studies, we investigate whether concentrated owners help or try to grab benefits from their firms during times of crisis. We find evidence suggesting that concentrated owners generally extend a helping hand, and thus boost firm performance, during crisis. However, certain qualifications apply: Institutional development, which varies considerably across the 4 continents represented in our primary studies, has a varied impact on the focal relationship. We find that the helping tendencies of concentrated owners during crisis are positively moderated by the development of financial markets and the size of a nation’s informal economy, but are negatively moderated by the presence of legal institutions designed to curb the discretion of concentrated owners. Thus, institutions can facilitate or hinder the helping hands of concentrated owners during crisis. Also, the performance effect varies considerably depending upon identity of owners. We find that inside owners and stable owners extend a helping hand to firms during crisis, but market owners do not. Furthermore, only inside owners continue to have the same (positive) effect on performance during non-crisis periods, during which stable and market owners have just the opposite effect.
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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 | 0.032 | 0.096 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.013 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".