Start-ups within entrepreneurial ecosystems: Transition towards a circular economy
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
This article explores the role of start-ups within entrepreneurial ecosystems in driving the transition towards a circular economy. It emphasises the importance of understanding and supporting circular start-ups for broader sustainability impacts. Unlike established firms, start-ups can readily adopt ambitious circular business models (CBMs) without the risk of business model cannibalisation and with the agility to adapt to market trends. CBMs enhance value creation, delivery and capture resource flows in an optimised non-linear fashion. Scaling up CBMs is crucial for overall economic, social and environmental benefits. Hence, leveraging the key entrepreneurial ecosystems actors, such as universities, business incubators and related venture development intermediaries, is vital for start-up support. In this special issue, we have invited researchers to submit contributions that delve into the dynamics among start-ups, entrepreneurial ecosystems and the circular economy, aiming to enrich our understanding of the early stage start-up development process with the aim of promoting the circular economy at a firm, regional or national level.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it