Bibliographic record
Abstract
The free flow of the Fraser River bears the consequences of history but reveals none of its causes. Over the twentieth century, this river has played host to dreams of liberation and transformation, to physical changes and social consequences, to protective actions and inactions. Yet, against the predictions of most observers in the early and middle parts of the century, the river runs freely in its main course. The river plays host to dreams, but not to large dams. From a comparative perspective, this outcome is surprising. In the regional context of western North America, the Columbia River, the Fraser's closest parallel case, bears the weight of sixteen main-stem dams. Among Canada's largest rivers, only the Mackenzie River remains, like the Fraser, undammed. Within BC, smaller rivers such as the Stikine, Nass, and Skeena have not been dammed on their main stems, but they contain much smaller power potential, lie at a distance from major centers of population, and provide habitat, like the Fraser, for major salmon runs. Over the twentieth century, Canadians have dammed rivers across northern North America from the Saguenay to the St. Lawrence to the Saskatchewan, and executed over fifty interbasin transfers, some on a massive scale. In the northern third of the world, according to Dynesius and Nilsson, there are only five other rivers of comparable size with the Fraser that experience little or no fragmentation in their main channels.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.174 | 0.049 |
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".