Urban Slavery in West and West Central Africa during the Transatlantic Slave Trade
Bibliographic record
Abstract
The trade in enslaved captives across the Atlantic Ocean shaped West and West Central Africa’s urban shoreline. Towns adjusted to or were created for service to that trade. In turn, these towns shaped the socioeconomic realities of their hinterlands. Between the seventeenth and nineteenth centuries, this impact was felt nowhere more than among the enslaved and freed-slave migrants who made their way to perceived opportunities on the coast. This article examines these migrants’ experiences through a comparative regional approach. We look first at Saint Louis du Senegal and then compare the Gold Coast, Whydah, Lagos, the Bight of Biafra, Luanda, and Benguela. Each of these cities had its own particular qualities, often shaped by geography, but there were also common features. They all depended heavily on slave labor and, in several, female slave ownership was important. Most significantly, slavery in these cities was marked by considerable autonomy for the enslaved.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".