Building sustainable circular agriculture in China: economic viability and entrepreneurship
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
Purpose In the context of China, the purpose of this paper is to empirically answer three related questions: Could circular agriculture (CA) attain economic, ecological and social benefits simultaneously? What is key to a successful CA business in emerging economies? And who plays the vital role in building and sustaining a circular business? Design/methodology/approach The paper is based on a field study and looks at a farm in China. It uses a triangulation methodology to collect information. Besides longitudinal filed work at the farm, the researchers have also interviewed multiple stakeholders and conducted field research at the local markets. Findings With concrete performance data, the study proves that a circular approach can help achieve ecological, economic and social goals together. It shows that economic viability is essential to succeeding in circular operation, sufficient production pathways are required to make such operation sustainable, and entrepreneurship is key to build and grow a circular business. Research limitations/implications The findings point to the crucial role of entrepreneurship in promoting the circular model in emerging economies. These findings, however, may not be readily generalizable, given the limitations of the case study approach. Practical implications The study highlights a few areas in which government assistance can make a difference, including financial incentives, information provision, technical support and most importantly the creation of a positive environment for entrepreneurial development. Originality/value While prior research emphasizes the role of government in promoting circular economy in developing and emerging markets, the study proves that entrepreneurship is key to turning government initiatives into economically viable and sustainable circular operation.
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 | 0.001 | 0.000 |
| 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 | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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