Beyond engineering: A review of reservoir management through the lens of wickedness, competing objectives and uncertainty
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
Traditionally, reservoir management has been synonymous with the operation of engineering infrastructure systems, with the majority of literature on the topic focusing on strategies that optimize their operation and control. This is despite the fact that reservoirs have major impacts on society and the environment, and the mechanics of how to best manage a reservoir are often overshadowed by both environmental changes and higher-order questions associated with societal values, risk appetite and politics, which are highly uncertain and to which there are no “correct” answers. As a result, reservoirs have attracted more controversy than any other type of water infrastructure. In this paper, we address these often-ignored issues by providing a review of reservoir management through the lens of wickedness, competing objectives and uncertainty. We highlight the challenges associated with reservoir management and identify research efforts required to ensure these systems best serve society and the environment into the future.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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