Value Added by Angel Investors through Postinvestment Involvement: Exploratory Evidence and Ownership Implications
Bibliographic record
Abstract
Abstract This article uses data from The Performance Project: Group Angel Investor, released by the Kauffman Foundation and the Angel Capital Education Foundation in 2007 to investigate the value added by angels through their postinvestment involvement (PII) with ventures. In contrast with findings showing that venture capitalist PII may not significantly affect venture performance, the results show that the PII of angels contributes significantly to value creation. The value added is due to involvement related to mentoring rather than monitoring. This resultant value added has a very important implication for the ownership share that angel investors deserve or, conversely, the share that the entrepreneurship retains. It is an important factor missing in current discussions about the ownership share that entrepreneurs must surrender in exchange for equity capital. The article discusses the implication conceptually and proposes an adjustment to the model proposed in the literature to determine the theoretical ownership share that entrepreneurs deserve to retain.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".