Bibliographic record
Abstract
The Pages of Resistance exhibition project is a digital humanities and public history project dedicated to the study of slavery and rebellion during the slave trade era, occurring in Latin America and the Caribbean during the 1800s. Its focal point is the curation of a travelling exhibition on enslaved Muslim African literacy, conceptualized in this paper as a form of spiritual resistance to bondage. The inspiration for this project is based on the digitization of three sets of nineteenth-century Qur’anic and non-Qur’anic manuscripts found on the bodies of enslaved Muslim Africans after they perished the night of the Malês rebellion in January 1835 in Bahia, Brazil. The Pages of Resistance exhibition project, which currently concentrates on Brazil, is a part of a broader initiative that is focused on Muslim African diasporic history during the Atlantic slave trade era. It is a collaborative initiative between cross-disciplinary researchers and creative producers engaging in digital scholarship and multimedia art production. This article discusses the concept and Public History of the Pages of Resistance project as well as the context in which it is situated, and it describes the methods applied in the research process of this multilingual initiative. In doing so, this project reflects other anti-racist initiatives in the field of public history, situating itself between the intersections of Blackness, memory, religion, and resistance by marginalized groups and minorities.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.266 | 0.058 |
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".