Understanding rivers and their social relations: A critical stepto advance environmental water management
Bibliographic record
Abstract
River flows connect people, places, and other forms of life, inspiring and sustaining diverse cultural beliefs, values, and ways of life. The concept of environmental flows provides a framework for improving understanding of relationships between river flows and people, and for supporting those that are mutually beneficial. Nevertheless, most approaches to determining environmental flows remain grounded in the biophysical sciences. The newly revised Brisbane Declaration and Global Action Agenda on Environmental Flows (2018) represents a new phase in environmental flow science and an opportunity to better consider the co‐constitution of river flows, ecosystems, and society, and to more explicitly incorporate these relationships into river management. We synthesize understanding of relationships between people and rivers as conceived under the renewed definition of environmental flows. We present case studies from Honduras, India, Canada, New Zealand, and Australia that illustrate multidisciplinary, collaborative efforts where recognizing and meeting diverse flow needs of human populations was central to establishing environmental flow recommendations. We also review a small body of literature to highlight examples of the diversity and interdependencies of human‐flow relationships—such as the linkages between river flow and human well‐being, spiritual needs, cultural identity, and sense of place—that are typically overlooked when environmental flows are assessed and negotiated. Finally, we call for scientists and water managers to recognize the diversity of ways of knowing, relating to, and utilizing rivers, and to place this recognition at the center of future environmental flow assessments.
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How this classification was reachedexpand
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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".