Disciplining Disobedient Subjects: The Punishment of Aleppo’s Insurgents in 1850 as a Contentious Issue
Bibliographic record
Abstract
This paper draws on research conducted for the project Stories of Survival: Recovering the Connected Histories of Eastern Christianity in the Early Modern World, which is supported by funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement number 638578). 1 Anonymous, Ḥawādith mā tawaqqʿa min al-ghawāyil bi-maḥrūsat Ḥalab al-shahīra fī l-yawm al-sādis ʿashar min shahr tishrīn awwal gharbī sanat 1850, ed. in Feras Krimsti, Die Unruhen von 1850 in Aleppo: Gewalt im urbanen Raum (Berlin: Klaus Schwarz, 2014), 399 (German translation, 422-23). 2 Studies on the 1850 uprising include Krimsti, Die Unruhen; idem, "The 1850 Uprising in Aleppo: Reconsidering the Explanatory Power of Sectarian Argumentations", in Urban Violence in the Middle East: Changing Cityscapes in the Transition from Empire to Nation State, ed. by Ulrike Freitag et al. (New York: Berhahn, 2015), 141-63; Bruce Masters, "Aleppo's Janissaries: Crime Syndicate or Vox Populi?", in Popular Protest and Political Participation in the Ottoman Empire: Studies in Honor of Suraiya Faroqhi, ed. by Eleni Gara et al. (Istanbul: Bilgi University, 2011), 167-175, idem, Christians and Jews in the Ottoman Arab World: The Roots of Sectarianism (Cambridge University Press,
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.021 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.007 |
| 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".