Unleashing circular economy potential in agriculture: Integrating social impact assessment with the <scp>ReSOLVE</scp> framework as a tool for sustainable development
Bibliographic record
Abstract
Abstract The circular economy concept has grown in popularity in recent decades as a potential method to offset the waste produced by the linear economy model. In this study, the authors proposed an update to the ReSOLVE framework that includes social impacts and uses decision variables based on the ECOGRAI methodology to facilitate a system‐wide analysis to support sustainable decision‐making. After the updated framework was outlined, it was employed in a theoretical case study to evaluate the current state of the poultry industry and determine hotspots where circular economy metrics could be implemented to benefit affected stakeholders. While the poultry sector was used as a case study, the proposed framework can be applied with modified indicators in other agricultural sectors. This work demonstrated that decision makers can improve the agriculture sector's high social and environmental impact by applying a framework that integrates ReSOLVE circular economy principles and social impact assessment methods.
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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 | 0.013 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.004 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".