Bibliographic record
Abstract
Trade and commercial development in the Atlantic world required capital, investment, and financing, both directly and indirectly. Credit was allocated, extended, used, and abused to further growth in various commercial sectors. The circulation of capital was a requisite feature of trade activity, with implications on both sides of and across the Atlantic. It was also a very social activity involving networks of partners and players across time and space. Issues of credit and debt cannot be isolated, therefore, from the broader institutional context: technical, social, and cultural. This article presents selected readings on the role played by credit (and debt) in the economic development of the Atlantic world. The scope is restricted to private rather than public credit, and to the long 18th century. Readings reinforce the nature of credit operations across the Atlantic, including merchant trade, the organization of the slave trade, and agricultural production in the colonies; and within Europe, as merchants and traders sought out operating credit and refinancing of trading activities. The nature of credit and debt cannot be understood without some appreciation for the technical tools, mechanisms, institutions, and laws in which these systems operated. Equally, credit networks were social relations within extensive and extended networks of actors subject to social and cultural norms. These norms can be apprehended more readily through the examination of the attitudes, perceptions, and values of those involved in granting and securing credit. Credit evokes questions of confidence, insolvency, risk, reputation, and trust. How these concepts were interpreted, perceived, and operationalized are important in understanding the evolving nature of the broader institutional context. Finally, while not exhaustive, this entry incorporates readings that provide a comparative dimension to this history, enabling the reader to tease out the parallels in different national histories, the divergent adaptations in various settings and contexts, from which it is possible to weave a common thread to the story of credit and debt in the 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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.025 | 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".