Bibliographic record
Abstract
Islam in North America is now a fact and the three million Muslims living in this part of the world provide definite proof of its establishment in the pluralistic democratic societies of Canada and the United States. The history of this religion can be traced back several centuries. There are scholars who believe that the earliest encounters of Islam with the New World predate the age of Columbus. Working on certain literary fragments of Arab writers of pre-Columbian times, in western Sudan, these scholars maintained that an expedition was outfitted and sent out by Abu Bakr and Mansa Kankan Musa who ruled the ancient empire of Mali. This hypothesis about pre-Columbian Muslim arrival in the New World was also supported by Harvard University Professor Leo Wiener, who argued in the 1920s that Arabo-Islamic and Mande influences began during this period. Instead of relying on Arabic literary fragments to develop his case for a pre-Columbian Muslim arrival in the New World, Leo Wiener based his conclusions on linguistic evidence derived from an analysis of the languages in Mexico and areas of Mande peoples in West Sudan. Though Wiener wrote a longer study arguing his point, he failed to convince the mainstream American historians. To most of these scholars, the arrival of Islam dates back to the slave trade when many African Muslims began to arrive on the American shores. Allan D.Austin has done an excellent job of bringing together all the available literary fragments which deal with the life and experiences of Muslim slaves in North America. This work shows that many of the Muslims who came to America were literate and had some knowledge of the Qur’an and Islamic teachings. Apart from the much celebrated Kunta Kinteh whose saga has been fictional-ised and immortalised by his descendant, Alex Haley, there were men like Ayub Ibn Sulayman Diallo, Yarrow Mamout (which should read Yorro Mahmud), Muhammad Bah and others whose stories were recorded by contemporary writers.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".