Lost in Development's Shadow: The Downstream Human Consequences of Dams
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 World Commission on Dams (WCD) report documented a number of social and environmental problems observed in dam development projects. The WCD gave particular emphasis to the challenges of properly resettling populations physically displaced by dams, and estimated the total number of people directly displaced at 40-80 million. Less attention has been given, however, to populations living downstream of dams whose livelihoods have been affected by dam-induced alterations of river flows. By substantially changing natural flow patterns and blocking movements of fish and other animals, large dams can severely disrupt natural riverine \nproduction systems ??? especially fisheries, flood-recession agriculture and dry-season grazing. We offer here the first global estimate of the number of river-dependent people potentially affected by dam-induced changes in river flows and other ecosystem conditions. Our conservative estimate of 472 million river-dependent people living downstream of large dams along impacted river reaches lends urgency to the need for more comprehensive assessments of dam costs and benefits, as well as to the social inequities between dam beneficiaries and those potentially disadvantaged by dam projects. We conclude with three key steps in dam development processes that could substantially alleviate the damaging downstream impacts of dams."
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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