Hegemonic modernity: the Middle East and North Africa during the nineteenth and early twentieth centuries
Bibliographic record
Abstract
The background By the end of the sixteenth century, three Muslim empires ruled large and prosperous territories throughout Asia, Europe and Africa. To the east stood the Mughal Empire, to the west, the powerful Ottoman Empire, and at the center, stretching over the Iranian plateau, the Ṣafavids. Between 1709 and 1739, the Ottomans engaged in four relatively successful wars that seemed to prove their military competence against Russia and the central European states. The peace that prevailed during the next three decades also seemed to convince the Ottomans of the superiority of their military power, even as Europe during this very period was embarking on one of the most rapid advances in military technology, military discipline and organization. However, the ensuing three wars with Russia, ending in 1774, 1792 and 1812, resulted in crushing Ottoman defeats, as well as the loss of the northern shores of the Black Sea and Crimea. By the last of these wars, Arabia and Egypt had defected, the former taken by the Wahhābites and the latter by Muḥammad ʿAlī. The Empire appeared on the verge of crumbling. The stunning military defeats starting during the last third of the eighteenth century spurred a new wave of Ottoman concessions ( imtiyāzāt ) that were to continue, and build upon, the benevolent capitulations granted to a number of European states during the preceding centuries.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".