Negotiating Niagara Falls: US-Canada Environmental and Energy Diplomacy
Bibliographic record
Abstract
Niagara Falls is one of the world’s most iconic natural features. Yet in many ways Niagara Falls is decidedly unnatural, for the United States and Canada physically manipulated this waterfall over the course of the twentieth century so that its waters could be diverted for hydropower production while still ostensibly retaining the cataract’s aesthetic beauty for tourism. While this appears contradictory, since the latter depends on ample amounts of water flowing over the Falls while the former requires water going around the Falls, experts believed that they could engineer a compromise and essentially fool the public. Following the 1950 Niagara River Diversion Treaty, the two North American nations constructed hydroelectric stations and remedial works (various engineering interventions including excavations, fills, reclamations, weirs, and dams) at Niagara Falls that allowed for the majority of the water volume to be diverted for power production. Moreover, the largest of the Niagara cataracts,...
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How this classification was reachedexpand
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".