Hydropower Dams and the Human Right to Water: an Operational Transdisciplinary Assessment Framework
Bibliographic record
Abstract
There is growing urgency for actionable and standardized approach to human rights assessments of hydropower dam constructions and operations that incorporates multiple dimensions of the right to water. Yet, the water issues faced by affected communities are determined by local contexts and therefore challenging to map to universal norms like human rights in a way that is both objective and transferrable. Conversely, the human right to water extends beyond the narrow dimensions of water access and availability and also includes cross cutting obligations (e.g, self-determination and non-discrimination) and inter-related rights (e.g., rights to health, healthy environment and livelihood). The nearly universal scope of human rights with respect to water makes them challenging to apply without an operational framework to systematically diagnose challenges to their implementation in practical settings. The framework that we present addresses both challenges with a procedure to systematically diagnose multiple key dimensions of inadequate water access (e.g, green, blue and economic water scarcity or excess) and governance failures (e.g., power asymmetry or threats to hydrosocial relations). The framework then maps the diagnosed issues to specific challenges to implementation of human rights that account for their multi-dimensional nature. This work is a unique transdisciplinary collaboration between water intensive industries and experts from the fields of hydrology, governance, and human rights law. We apply the framework to representative international hydropower cases (e.g., the Lower Sesan 2 Dam in Cambodia, the Muskrat Falls Dam in Canada) to synthesize key insights on the relationship between human rights and the impacts of hydropower projects on water security and governance.
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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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 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 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".