“Something Is Wrong Here”: An Interview With Sarah Cox About Damming Canadian Rivers for Hydroelectricity
Bibliographic record
Abstract
Only one-third of the world’s rivers remain free flowing, and one million species face extinction. In the climate crisis, the race for “clean energy” is on. Over the last century, the Canadian government has built hundreds of hydropower dams and is pushing ahead with more big dams despite decades of science showing their irreversible and significant social, environmental, and economic harms. Canada markets its hydropower as “clean” and “renewable.” In her book, Breaching the Peace: The Site C Dam and a Valley’s Stand Against Big Hydro, journalist Sarah Cox documents the externalities caused by Canada’s megadams and the ongoing struggle by indigenous people, farmers, and activists to stop one of the largest and most controversial dams located on the Peace River in British Columbia, Canada. Meg Sheehan, environmental attorney, interviewed Cox during the COVID-19 pandemic to get the story behind Canada’s hydropower policy and how things can change.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.054 | 0.009 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.010 | 0.020 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".