Venture Capital Networks and Investment Performance in <scp>C</scp>hina
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Bibliographic record
Abstract
We investigate the relationship between venture capital ( VC ) networks and investment performance in C hina. Distinct features of C hina's VC networks are captured in our econometric model through the inclusion of an index of network stability and a dummy variable that indicates a VC firm's connections with the C hinese state. Our econometric analysis shows that a VC firm's position in its network, its network stability and close connections with the state all contribute to its investment performance. Comparison with the findings in H ochberg et al . (2007) indicates that networks are more important for investment performance in C hina than in the US . Moreover, our analysis suggests that familiarity with local culture and customs and understanding of the idiosyncrasies of C hina's markets and institutions are important for the success of a VC firm in C hina.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it