Reliability and risk in new ventures: Founding team's native immigrant composition and performance variability
Bibliographic record
Abstract
Abstract The study examines the performance and the risks of new ventures founded by hybrid teams consisting of immigrants and natives. Earlier investigations have taken a dichotomous view of immigrants in the founding team without paying sufficient attention to their relative numbers. We argue that the numeric strength of immigrants in the founding team affects firms' average performance. Furthermore, as entrepreneurial endeavors are risky, we examine the native/immigration effect on the new venture performance variability. Using new venture data from the Kauffman Firm Survey, we find that the ratio of natives in the founding team is associated with lower mean performance and higher risk in the short and medium term. This means a higher relative number of immigrants in the founding team is associated with higher average performance and lower risk. We further find that the average team age is negatively associated with the short‐ and medium‐term mean performance while positively affecting the short‐term performance variability. A higher male–female ratio is positively associated with performance but not with variability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 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".