Bibliographic record
Abstract
Abstract Throughout the slave trade era, wars and raids in the hinterlands of West Africa brought captives into different ports of the Atlantic coast, many of whom were Muslims. Various political and social factors in Africa influenced the nature of the transatlantic slave trade, including the identities of those involved in exporting enslaved Muslims, the number of people transported, their ethnic origins, and the colonies and countries to which they were shipped. These dynamics shaped the trade’s complexity across different regions. Following the literary developments in Europe, the collection of individual histories of slavery began in North America in the first decades of the 18th century. Abolitionist biographical accounts were written about the enslaved (overwhelmingly about male individuals) as well as autobiographies in Arabic and English produced by freed Muslim Africans in Maryland, South Carolina, North Carolina, Georgia, Alabama, and Mississippi, as well as Québec and Canada West (present-day Ontario). In the Caribbean, Arabic and Hausa-Ajami manuscripts were produced both on the islands and on the shores of Central America. Freed and enslaved Muslim Africans in Brazil, particularly those from Central Sudan, created long-standing and rebellious communities. The Malê Uprising of 1835 was a cornerstone event for slave resistance and marked the strengthening of the bonds of a transnational community of Muslim Africans in different parts of Brazil that had an enduring impact until the early 20th century. Community practices as well as religious and cultural pluralisms marked the histories of these diverse diasporas.
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 | 0.001 | 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 | 0.006 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".