In the Eye of All Trade: Bermuda, Bermudians, and the Maritime Atlantic World, 1680-1783
Bibliographic record
Abstract
Until recently, historians of the colonial Americas largely reproduced imperial assessments of Bermuda's supposedly truncated development, seeing in the early exhaustion of the tiny colony's tobacco economy a more general failure of the place. In this superb and rewarding book, Michael J. Jarvis carefully uncovers the improvised and familial strategies that Bermudians evolved as they quickly turned outward to the sea and to the hinterlands and the ports arrayed along an Atlantic rim from Newfoundland to the Windward Islands, all of which lay within one thousand miles of Bermuda. Many of these Bermudian engagements with a maritime Atlantic have been known for some time, but the details have never been so fully revealed or situated in such a rich maritime social history. With few material resources at home, by the end of the seventeenth century Bermudians turned their backs on the imperial center and profitably employed their fast sloops in carrying trades, smuggling, and resource extraction in the largely unmonitored border zones that Jarvis conceives of as an Atlantic commons. In exploiting this world in motion, Bermudians drew on persistent kinship linkages made in early outmigration from the colony (rightly seen here as a strength) to develop the kinds of self-organized, decentralized networks now seen as characteristic of the early modern Atlantic world.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".