The Mortal Sea: Fishing the Atlantic in the Age of Sail
Bibliographic record
Abstract
Overfishing is often thought of as a contemporary problem. Jeff Bolster’s presentation reveals humans transforming the sea long before factory trawlers turned fishing from a hand-liner’s art into an industrial enterprise. The western Atlantic’s legendary fishing banks, stretching from Cape Cod to Newfoundland, have attracted fishermen for more than five hundred years. In his innovative re-telling of that supposedly well-known sea story, Bolster, a historian and professional mariner, reveals possibilities unlocked through a focus on Environmental Humanities. Blending marine biology, ecological insight, and a remarkable cast of characters — from notable explorers to scientists to an army of unknown fishermen — this talk, based on his book of the same name, illuminates a story that is both ecological and human: the prelude to an environmental disaster. Jeffrey Bolster is a Professor Emeritus of History at the University of New Hampshire. His expertise lies in the areas of maritime history, early American history, African American history, New Hampshire history, and environmental history of Northwest Atlantic commercial fisheries. Bolster states he “is equally at home with a deck under [his] feet or with the treasures of a research library spread before [him].” He is the author of a number of publications including the best-selling book, Black Jacks: African American Seamen in the Age of Sail and his most recent book, The Mortal Sea: Fishing the Atlantic in the Age of Sail. The latter won the American Historical Association’s 2013 Albert J. Beveridge Prize and 2013 James Rawley Prize in Atlantic History. The book also won the North American Society for Oceanic History’s John Lyman Book Award for the best book in U.S. Maritime History. Columbia University named Bolster one of two recipients of the 2013 Bancroft Prize, which is considered one of the most distinguished academic awards in the field of history.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.008 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".