3E + 3B: An Elaborated One Health Approach to Bridging the Researcher-Stakeholder Disconnect at the Food-energy-water Nexus Within Circular Bioeconomies
Bibliographic record
Abstract
The food-energy-water (FEW) nexus presents a complex set of challenges as it recognizes the profound and intricate interdependence of food production, energy generation, and water resources as well as the role of people in these systems. Managing issues at this nexus and within circular bioeconomies requires a highly integrated and transdisciplinary approach to successfully frame the problem and investigate sustainable solutions. A One Health approach applies this type of systems theory at the local, regional, national, and global levels with the goal of achieving optimal health for people, animals, plants, and their shared environment. However, there often remains a disconnect between stakeholders and researchers in both the research development and research product implementation stages. To address that, we propose a complimentary framework including 3 “E”s (Earn trust, Explore fears, and Educate) and 3 “B”s (Build partnerships, develop Business models, and Bear the perceived risks) to bridge that researcher-stakeholder disconnect.
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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 | 0.046 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.010 | 0.036 |
| Scholarly communication | 0.017 | 0.013 |
| Open science | 0.005 | 0.019 |
| Research integrity | 0.015 | 0.012 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".