Bibliographic record
Abstract
Richard Ravalli's Sea Otters tells the story of Enhydra lutris in the northern Pacific Ocean over three centuries. This concise volume deftly tackles the relevant histories of Russia, China, Japan, the United States, Canada, and Mexico. The author draws upon no manuscript collections but instead a broad range of materials, from conservation and ecology science to narratives of trade and exploration to government materials and newspapers to recent popular primary sources. As a work of quasi synthesis, this book helpfully lays a foundation that will certainly support later archival work on sea otters and related species who inhabited the same Pacific Rim ecosystems. Along with the author's attention to many new stories from the Pacific world, the volume reveals some important historical lessons: that imperial expansion and regional otter extinction were directly connected as diplomacy and global trade intersected with the day-by-day decisions of hunters; that “the sea otter trade—for better or worse—revolutionized Pacific communities by introducing them to global capitalist systems from which they had been disconnected prior to the late eighteenth century” (p. 61); the cruel historical irony that, due to their near destruction of the species in many places, nineteenth-century hunters were the only ones who knew enough about otter behavior to inform early conservation policies of that era; and, a truism of animal history in general, that one species can receive multiple human interpretations over time and space—in sea otters' case, as predator, prey, endangered population, internet cutie, and aquarium marketing mascot.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".