Venture Capital Financing of Entrepreneurship: Theory, Empirical Evidence and a Research Agenda
Bibliographic record
Abstract
Entrepreneurial activity in North America has steadily increased in the past few decades. For example, the rate of new business registrations in Canada approximately doubled between 1979 and 1989 alone. The entrepreneurial sector is particularly interesting because of its close relationship to innovation and technological progress and the perception that it is the “engine of growth” of the economy in the sense that the entrepreneurial sector is a disproportionate supplier of employment growth. It follows from this perception that modern economies would thrive on a healthy and vibrant entrepreneurial business sector. Despite the observed growth in business initiation, however, only one new firm in five in Canada survives for ten years or more. And of the 80 percent of new ventures that cease operations within a decade, half of those fail within the first two years. Gaps or failures in financing the entrepreneurial sector may account for the observed high failure rates of new businesses.
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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 | 0.008 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".