Replicating Davidsson and Honig (2003): Updates on Human Capital, Social Capital, and Replications in Entrepreneurship
Bibliographic record
Abstract
We conducted a three-step replication of Davidsson and Honig’s study on the roles of human and social capital in venture creation processes. First, we attempted an exact replication to rule out mistakes and questionable manipulations influencing the original results. Second, we included the initial stage of development as an additional control variable, reflecting on updates suggested in later research. Third, we extended the original analyses using a sample from a different spatiotemporal context, enhancing theoretical generalizability. We largely validate D&H’s findings, highlight the importance of modeling initial entrepreneurial processes, and emphasize the underappreciated complexities and value of replication studies.
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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 | 0.173 | 0.482 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".