Bibliographic record
Abstract
Winner of the 2014 Albert Corey Prize from the American Historical Association Winner of the 2013 Hal Rothman Award from the Western History Association Winner of the 2013 John Lyman Book Award in the Naval and Maritime Science and Technology category from the North American Society for Oceanic History For centuries, borders have been central to salmon management customs on the Salish Sea, but how those borders were drawn has had very different effects on the Northwest salmon fishery. Native peoples who fished the Salish Sea--which includes Puget Sound in Washington State, the Strait of Georgia in British Columbia, and the Strait of Juan de Fuca--drew social and cultural borders around salmon fishing locations and found ways to administer the resource in a sustainable way. Nineteenth-century Euro-Americans, who drew the Anglo-American border along the forty-ninth parallel, took a very different approach and ignored the salmon's patterns and life cycle. As the canned salmon industry grew and more people moved into the region, class and ethnic relations changed. Soon illegal fishing, broken contracts, and fish piracy were endemic--conditions that contributed to rampant overfishing, social tensions, and international mistrust. The Nature of Borders is about the ecological effects of imposing cultural and political borders on this critical West Coast salmon fishery. This transnational history provides an understanding of the modern Pacific salmon crisis and is particularly instructive as salmon conservation practices increasingly approximate those of the pre-contact Native past. The Nature of Borders reorients borderlands studies toward the Canada-U.S. border and also provides a new view of how borders influenced fishing practices and related management efforts over time. Watch the book trailer: http://www.youtube.com/watch?v=7ffLPgtCYHA&feature=channel_video_title
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.020 |
| Scholarly communication | 0.020 | 0.017 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.020 | 0.004 |
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".