Bibliographic record
Abstract
Enslaved Muslims constituted a relatively small proportion of the enslaved population in the Americas, and that population was largely male. This article explores an unappreciated dimension of the background of these enslaved Muslims, the fact that most came from towns and had traveled widely, between towns; that is enslaved Muslims tended to come from urban settings, no matter where they ended up in the Americas. This urban background has implications in terms of the experiences and expectations of the enslaved. The urban context was associated with commerce, craft specialization, literacy, and political and social consciousness of slavery and its meaning within west Africa. The study examines available biographical information on enslaved Muslims from the Western Sudan, usually referred to as Mandingo or some variant in the Americas, and those from the Central Sudan, including Hausa, Yoruba, Nupe and people from Borno. The urban setting of Muslim areas of West Africa is then compared with other towns and cities in the Atlantic world during the eighteenth and nineteenth centuries in terms of size of towns and multicultural backgrounds of urban populations, further demonstrating that the urban background of many enslaved Africans and the extent to which the enslaved population was moved between towns has not been appreciated.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".