Addressing climate change in EIA legislation and the climate-proofing of dams: a comparative analysis of Canada, Oman and Portugal
Bibliographic record
Abstract
Dams are long-term structures still being developed despite the controversy around their relevance and associated impacts. Dams can impact climate change but also be vulnerable to climate change risks when not properly assessed before approval. As including climate change within EIA is said to thrive this assessment, legislation is being revised and support guidelines adopted, but the practice remains scarcely researched. This article analyses how climate change is being addressed in EIA legislation, supporting guidelines, and dam safety regulations in Canada, Oman and Portugal. The findings show that climate change concerns are not fully detailed in the process, leaving aside references in steps like scoping and follow-up. Also, adaptation is disregarded in legislation and left to the guidelines. To make matters worse, the existing dam safety regulations are not including specific references to climate change. Given dams’ relevance and long-term nature, these conclusions underline the need to foster a clear inclusion of climate change concerns in the environmental assessment of new dams and ensure their climate-proofing before approval.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".