A semi-qualitative approach to the operationalization of the Food–Environment–Energy–Water (FE<sup>2</sup>W) Nexus concept for infrastructure planning: a case study of the Niger Basin
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
The countries sharing the Niger River suffer from poor access to clean water and energy as well as food insecurity. The Niger River Basin Authority is tasked with advancing progress in all these areas while also reducing environmental degradation. To help the basin authority and its investors prioritize portfolio activities that support multiple securities of interest, we developed a mixed-methods approach that engaged basin countries in qualitatively ranking projects to meet energy, environmental and food security goals, complemented by quantitative modelling for the more complex ranking of water and environmental sustainability goals, necessitated by complex upstream–downstream linkages.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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