The Quest for Modernity in the Middle East and the Islamic World Memories of State: Politics, History, and Collective Identity in Modern Iraq; The Future of Kurdistan in Iraq; Nationalism and Minorities Identities in Islamic Societies; and Muslims and Modernity: An Introduction to the Issues and Debates
Bibliographic record
Abstract
The Quest for Modernity in the Middle East and the Islamic World Memories of State: Politics, History, and Collective Identity in Modern Iraq, Eric Davis, Berkeley: University of California Press, 2005, pp. xi, 385. The Future of Kurdistan in Iraq, Brendan O'Leary, John McGarry and Khaled Salih, eds., Philadelphia: University of Pennsylvania Press, 2005, pp. xxi, 355 Nationalism and Minorities Identities in Islamic Societies, Maya Schatzmiller, ed., Montreal: McGill-Queen's University Press, 2005, pp. xiii, 346 Muslims and Modernity: An Introduction to the Issues and Debates, Clinton Bennett, London, New York: Continuum, 2005, pp. xviii, 286 These four books encapsulate a range of political issues that have shaped the formation of states and ideologies in the Middle East and North Africa since the beginning of the modern encounter between Europe and the Islamic world, from the Napoleonic invasion of Egypt through the post-World War I demise of the Ottoman world up to the American invasion of Iraq in 2003.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".