Hydropower Royalties: A Comparative Analysis of Major Producing Countries (China, Brazil, Canada and the United States)
Bibliographic record
Abstract
Hydropower is the leading renewable source of electricity generation and a low emission energy source. In order to be developed sustainably, it is important that its costs and benefits are adequately set and distributed. Different mechanisms, such as royalties, can be used for this purpose. Governments have usually kept hydropower royalty rates low, without internalizing negative externalities. This strategy is inefficient because it leads to larger electricity production and consumption, and hence exacerbates environmental impacts. This paper reviews the criteria proposed and used to set hydropower royalties. It also compares practices of the four main hydropower producers in the world: China, Brazil, Canada and the United States. Results show that royalty rates and distribution policies are determined in an arbitrary and unsystematic manner, but also that water use is usually undervalued. In order to encourage the development of this key renewable resource, in a sustainable and responsible way, national and international efforts should be made to rationalize and harmonize hydropower royalty rates.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".