Trade and Rivalry: The Promise of Expansion and Innovation during the 1630s
Bibliographic record
Abstract
In 1629 Sir George Calvert, first Lord Baltimore, visited Jamestown seeking a new refuge for a Catholic colony. A former Secretary of State under James I, Calvert resigned office following his conversion to Catholicism. During the early 1620s he established a small outpost on Newfoundland, where he settled with his wife and family in 1628. Defeated by the ‘sadd face of wynter’, he sought an alternative location in Chesapeake Bay. Robert Beverley subsequently noted that the settlers ‘looked upon him with an evil Eye, on account of his Religion’. Despite the hostile reception, on his return to England he secured royal approval for the creation of another colony in the Bay, named Maryland, in honour of Charles I's French wife, Henrietta Maria. Although Calvert died in April 1632, shortly before the charter for the settlement passed under the royal seal, his son Cecil, second Lord Baltimore, proceeded with the venture. By this ‘unhappy Accident’, bemoaned Beverley, a ‘Country which Nature had so well contriv’d for one, became Two separate Governments’. The establishment of Maryland transformed an emerging colonial world. It divided the Bay into rival colonies and competing interethnic trading associations and networks. At the same time the new colony threatened the prospect of colonial expansion in Virginia. Consequently, during the 1630s the Bay became a bitterly contested arena, where religious animosity inflamed the competition over trade and territory. The focal point for much of this rivalry was Kent Island, settled as a satellite of Virginia, but which after 1634 lay within the bounds of Maryland. Claiborne's ambitions to combine trade and plantation in the upper Bay were mirrored by those of the Maryland adventurers along the Potomac. Innovative schemes to develop the transatlantic trade in beaver skins thus occurred under challenging and competitive conditions. Colonial and native rivalries, which spilled over into Delaware Bay, fuelled commercial expansion, but from the outset there was a danger that these duelling ventures would frustrate the aims and ambitions of the other. The Kent Island joint stock from 1631 to 1634 Although studied from various perspectives, the Kent Island partnership has yet to be recognized as one of the most ambitious and novel fur trading ventures established by the English prior to the formation of the Hudson's Bay Company in 1670.
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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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.044 |
| Scholarly communication | 0.025 | 0.025 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.016 | 0.010 |
| Insufficient payload (model declined to judge) | 0.010 | 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".