Racio-national Imaginary and Discursive Formation of Arabo-Islamic Identity in al-Manār and al-Risālah: A Topic Modeling Study
Bibliographic record
Abstract
This article focuses on the dynamics of culture, language, and race as integral to the discourse on Pan-Islamist/Pan-Arabist national identification in Egypt during an era of drastic change in the Egyptian political and social spheres that set the stage for the current century that followed. Our approach draws on computational tool of topic modeling to probe relevant thematic discussions on the” conceptualization of race, language, culture, and identity by leading Arab-Muslim intelligentsia at a foundational moment that paved the way for Arab Nahḍah (modernity). Specifically, this analysis is meant to trace the intellectual development in the writings of Muḥammad Rashid Riḍā’s (1865-1935), which appeared in the magazine he edited, al-Manār ('The Lighthouse', 1898-1935), and those of Aḥmad Ḥasan al-Zayyāt’s (1885-1968), editor of al-Risālah (`The Messageʼ, 1933-1953), also a weekly magazine, both published in Cairo, Egypt. The study concludes that both figures sought to galvanize a largely hybridized Islamist/Arabist discourse as manifested in the clusteral paradigms of modelled topics.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".