Mobilization of Personal Social Networks and Institutional Resources of Private Entrepreneurs in China*
Bibliographic record
Abstract
Les auteurs examinent les liens micro et macroscopiques dans l'étude de l'économie en transition, en analysant la façon dont les entrepreneurs mobilisent leurs réseaux sociaux personnels intégrés à diverses institutions, afin de protéger leurs ressources d'affaires. Les résultats démontrent que les membres du réseau travaillant dans les organismes du gouvernement ou du parti jouent, en gros, un rôle essentiel dans l'obtention des ressources importantes comme les contacts gouvernementaux et l'information sur le marché et le financement. Ils démontrent aussi que les entrepreneurs utilisent différents membres de leurs réseaux pour différents types de ressources. Les auteurs discutent les différentes conséquences que cela entraine pour l'étude des réseaux et de l'économie en transition. This paper addresses the micro and macro link in studying transitional economy by examining how entrepreneurs mobilize their personal social networks embedded in various institutions to secure business resources. The results show that, by and large, network members working in government/party agencies play an essential role in obtaining important resources, such as those for government contact and market information/funding. The results also show that entrepreneurs utilize different members of their networks for different types of resources. Implications to the study of networks and transitional economy are discussed.
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How this classification was reachedexpand
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.008 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".