Support for Rapid-Growth Firms: A Comparison of the Views of Founders, Government Policymakers, and Private Sector Resource Providers
Bibliographic record
Abstract
This article considers how rapid-growth should besupported, specifically, the role of government. The goal of the research wasto develop a theoretical basis on which to identify guidelines for supportingrapid-growth firms on the basis of the perspectives of firm owners, policymakers, and private-sector resources providers (such as venture capitalists,bankers, and consultants). Interviews, responses to written questionnaires, andtranscripts of group discussions by a small number of firm owners, policymakers, and private-sector resources providers were collected and analyzedqualitatively to identify each group's perspectives. Analysis revealed that each group sees its role as critical. Policy makersand external resources providers have incentives to interact with rapid-growthfirms. Rapid-growth firms have incentives to obtain advice from governmentsources and external resources providers, but they prefer to obtain advice fromtheir peers. The findings suggest a network-bases approach to the support ofrapid-growth firms. (TNM)
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".