Islam's Low Mutterings at High Tide: Counter-Veiling Practices Across the Black Atlantic
Bibliographic record
Abstract
Recent scholarship on enslaved African Muslims in the Americas, by Allan Austin, Michael Gomez, and Sylviane Diouf, has explored African Muslim slave narratives in terms of ruined architecture; this paper, however, focuses on the sonic traces of such texts, specifically Omar ibn Saids slave narrative. By tracing the memory of slavery through the echoes of African Islam, this paper attends to the resistances to slavery in the Islamic soundscapes. In flirting with conversion, yet maintaining an obstinate theological stance, Omar deploys what I am calling counter-veiling as a technique of duplicity. While many scholars have traced the encoding of resistance within slave narratives, their work has disclosed the centrality of the blues as a predominantly Christian source of protest, a vernacular musical tradition that finds expression in the sorrow songs carefully transcribed in so many of these narratives, and which informs African American literary tradition. Landmark studies by Amiri Baraka, Houston Baker, and Paul Gilroy among others, have stressed the centrality of blues for black culture; and revealed how the partial notes sounded mournfully evoke a lost whole. The attunement to the sacred in the blues cannot be ignored; given that Christianity and Islam share a religious history, the inclusion of an Islamic sacred component to the blues highlights the overlapping of these religious frameworks.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".