Bridging the gap between the water-energy-food nexus and compound risks
Bibliographic record
Abstract
Abstract The water-energy-food (WEF) nexus is a concept and approach to examine the interactions of water, energy, and food resources. Similarly, compound risks are a set of risk types that consider multiple connected factors that amplify risks. While both concepts are promoted as approaches to move beyond silos and address complex problems in environmental governance, there has been limited exploration of their overlap. Our study integrates these two approaches for more holistic assessment and management of resources in the context of climate risks. We examine the connections between the WEF nexus and compound risk in two ways. First, we review the literature to identify previous conceptual connections between the WEF nexus and compound risks. Second, we review seven case studies with WEF nexus interactions and compound risks to identify how the two approaches might be considered in practice. Our results demonstrate that there is limited, though not non-existent, integration of the two concepts in both the theoretical literature and in the case studies. The four of the seven cases that do show some level of connection in practice demonstrate opportunities for greater integration in the future, such as leveraging the water sector as a bridge to address WEF nexus and compound risk challenges together.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.020 |
| Scholarly communication | 0.010 | 0.021 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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".