Alacrity: a new model for venture acceleration
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract As research on venture accelerators develops, different models have emerged in the literature. These focus on the goals of the accelerator, which range from creating profit for managers and building support for business platforms to promoting regional economic development, as well as on its organizational form based on its for-profit or non-profit status. This article examines a novel model, the networked venture builder model, which offers an alternative perspective on the acceleration process. Using the example of the Alacrity Global Ecosystem (AGE), this article explores how the venture builder model includes characteristics of multiple accelerator types, which has helped it both rapidly grow new ventures and achieve substantial economic development goals. Synergies between the different aspects of the AGE’s organizational design help it support multiple missions. Drawing on interviews with key stakeholders and entrepreneurs within the AGE, this article describes the history of the AGE and its present form, providing new insights into a novel, but increasingly common, accelerator design and laying the basis for further research on its emerging organizational form.
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.
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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it