Bibliographic record
Abstract
Abstract When Portuguese navigators reached the Senegal River in 1444, the region was already involved in the trans-Saharan slave trade. This meant that slaves were already part of Senegambian life as warriors, concubines, and farm workers. From the middle of the 17th century, demand for slaves in the West Indies led to an increase in prices and in the demand for slaves, which mostly came from the Bambara region of western Mali. The slave trade contributed to a series of Muslim revolutions as strict Muslim communities attacked both those laxer in their religious obligations and European colonizers. The trade in the Senegal River was in the 18th century dominated by female entrepreneurs known as signares. In the Gambia, juula traders brought slaves either to British factors or to James Island. Abolition in both Senegal and the Gambia began in the early 19th century but for long affected only areas under colonial rule. The process was a slow one because the expansion of peanut exports increased the demand for slaves and led to caution on the part of colonial regimes. Even after slavery was legally abolished in the early 20th century, the stigma of slave origins and some obligations persisted into the 21st century.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".