Bibliographic record
Abstract
Follows the trajectories of left-wing revolutionary movements across the Arab world Introduces new transnational and generational approaches in the study of Arab Left, and thereby opens new avenues for research on the Cold War, the Sixties and national emancipation struggles Features an interdisciplinary team of scholars that bring into conversation a wide range of concerns including radicalisation processes, revolutionary hopes, neoliberal globalisation, Islam and the Left, the legacy of Marxism, communism and Left-wing politics in general Examines the interventions of a wide range of leftist parties and groups in the Middle East Traces the political involvement of Arab Left revolutionaries such as Khaled Bakdash, Mahdi Ben Barka, Khalid Ahmad Zaki and Arwa Salih The Arab Lefts explores the entangled histories of Left-wing trends across the Mashreq and Maghreb regions in the ‘Long Sixties’. Based on an analysis of textual and audio-visual materials, it surveys radical Left traditions in the Arab world that took shape between the 1950s and 1970s. The book is divided into three thematic parts that are compiled of case studies utilising a multitude of perspectives in political theory, history, literary studies and sociology. In the first part, the authors study revolutionary circulations of men, representations, and know-how. The second part is devoted to interrogating the multifaceted tensions between local, regional, and global challenges. The final part scrutinises the transformations of political subjectivities and invites reflection on the general shift from a revolutionary configuration of temporality to the closure of time – and the so-called ‘Left Melancholy’. The result is a balanced account of Left-wing revolutionaries that provides new insights into the history of the Middle East as well as contemporary radicalisation processes and authoritarian rules. Contributors Orit Bashkin , University of Chicago, USA. Samer Frangie , Center for Arab and Middle East Studies, American University of Beirut, Lebanon. Nate George , Rice University, USA. Gennaro Gervasio , Università Roma Tre, Italy. Laure Guirguis , Aarhus University, Denmark; IREMAM, France. Jens Hanssen , University of Toronto, Canada. Sune Haugbolle , Roskilde University, Denmark. Jakob Krais , Gerda Henkel Foundation, Germany; Leibniz-Zentrum Moderner Orient (ZMO), Germany. Daniela Melfa , University of Catania, Italy. Hana Morgenstern , Cambridge University, UK; Newnham College, UK. Maha Nassar , University of Arizona, USA. Matthieu Rey , IREMAM, France; CNRS, France; Collège de France, France. Abdel Razzaq Takriti , Center for Arab Studies, University of Houston, USA. Philipp Winkler , Florida Atlantic University, USA.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.034 | 0.009 |
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".