Canadian hydropower and the U.S. energy transition: controversies, opportunities, and strategic research directions
Bibliographic record
Abstract
Recent modeling for the northeast United States suggests that the least-cost decarbonization pathway involves a combination of build-out of domestic renewables generation and increased intertie capacity with Canada. U.S. imports of Canadian hydropower have increased by > 1 TWh per year between 2007–2021 because it is a cost-effective and low-carbon alternative to domestic fossil fuel generation. Yet, increased interconnection capacity and imports are controversial and have been opposed by U.S. environmental groups and members of the public. Development of new hydroelectric reservoirs disrupts foodways and lifeways of Indigenous populations and has greenhouse gas impacts greater than wind and solar (though less than fossil fuel alternatives). Two recently cancelled hydropower transmission projects linking New England and Quebec, Canada demonstrate the need to better understand the gap between pathways that appear optimal from the perspective of energy systems modeling and the pathways that will ultimately be socially and environmentally acceptable. The experience of the northeast mirrors that in other parts of the U.S. where substantial resources have been invested in pursuit of renewable projects that are ultimately abandoned following mobilization of stakeholders with adverse interests or values. A research program integrating environmental and economic modeling seeks to resolve controversies surrounding the use of Canadian hydropower in U.S. energy transitions. This includes conceptual disputes over valuation of hydropower from existing reservoirs in cost-benefit analysis; debates over whether new transmission infrastructure stimulates new generation capacity; and analysis of the relative importance of different benefits and impacts to the public.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.011 | 0.013 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".