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Record W6908191921 · doi:10.25620/e230516

Translating Politics into Art and Literature in the Arab World

2023· other· en· W6908191921 on OpenAlexaboutno aff

Bibliographic record

VenueICI Berlin · 2023
Typeother
Languageen
FieldSocial Sciences
TopicMiddle East Politics and Society
Canadian institutionsnot available
Fundersnot available
KeywordsSectarianismPoliticsSpanish Civil WarDemocracyPower (physics)ConversationThe artsMusical

Abstract

fetched live from OpenAlex

This event with the eminent Lebanese public intellectual and critic Fawwaz Traboulsi draws on his long experience of organizing for and writing about a democratic future in the Arab world. It delves into the political role of art and culture, from the Lebanese civil war to the Arab uprisings and beyond. The wide-ranging conversation will revisit his war-time photo essay <em>Guernica-Beirut</em>, consider the theatre of Fayrouz and the Rahbani brothers in light of the politics of sectarianism in Lebanon and elsewhere in the region, and probe the extent to which popular culture can challenge neoliberal ‘culture talk’ about and in the Middle East. Fawwaz Traboulsi has taught History and International Affairs at the Lebanese American University and the American University of Beirut. He has been a visiting professor at New York University, the University of Michigan, Columbia University, New York University, and Vienna University and a fellow of St. Antony’s College, Oxford and the Wissenschaftskolleg zu Berlin. His publications include <em>A History of Modern Lebanon</em> (2007), <em>Soie et Fer. Du Mont-Liban au Canal de Suez</em> (2017), <em>Guernica-Beirut </em>(A Picasso Mural/An Arab City at War, 1987), <em>In Kan Baddak Ti`shaq</em> (Essays in Popular Culture, 2004), <em>Masrah Fayrouz Wal-Rahabinah</em> (The Musical Theatre of Feirouz and the Rahbani Brothers, 2007), <em>Al-Dimuqratiyah Thawra</em> (Democracy is a Revolution, 2011), <em>Al-Tabaqat al-Ijtima’iyyah wa-l-Sulta al-Siyassiyyha fi Luban </em>(Social Classes and Political Power in Lebanon, 2016), <em>Damm al-Akhawayn</em> (On Violence in Civil Wars , 2017), and <em>Sayks-Picot-Balfour: Ma wara’ al-Khara’it</em> (Sykes-Picot Agreement-Balfour Declaration: Beyond the Maps, 2018). Traboulsi is a long-time journalist and the editor of the <em>Bidayat Magazine</em>. Leyla Dakhli is senior researcher in Modern History at the French Center for National Research (CNRS). Her work deals with the study of Arab intellectuals and the social history of the South Mediterranean region, with a particular focus on the history of women. She also explores the history and politics of languages, archives, and revolts in Tunisia. She is the principal investigator of the ERC-founded programme DREAM (Drafting and Enacting the revolutions in the Arab Mediterranean — ERC-CO 2017 DREAM) and part of the Arab Council for Social Science working group, ‘Gendering the Archive in the Middle East and North Africa’, and the Berlin-based CO2LIBRI working group, ‘Conceptual Collaboration: Living Borderless Research Interaction’ (FU-HU-ZMO). Jens Hanssen is a professor of Middle Eastern History at the University of Toronto. He will serve as director of the Orient Institute in Beirut from July 2023 onwards. His research explores the cultural entanglements between Europe, North Africa, and the Middle East since the 19th-century Arabic reform and revival movement — <em>al-nahda al-‘arabiyya</em>. His publications include <em>Fin de Siècle Beirut</em> (2005), <em>A Clarion for Syria: A Patriot’s Call Against the Civil War of 1860</em>, with Hicham Safieddine (2019), <em>Arabic Thought beyond the Liberal Age </em>and <em>Arabic Thought against the Authoritarian Age</em>,<em> </em>both with Max Weiss (2016 and 2018), and the <em>Handbook of Contemporary North African and Middle Eastern</em> <em>History</em>, with Amal Ghazal (2020). He currently serves on the board of directors of MESA and is a member of the international advisory board of the Khalidiyya Library in East Jerusalem.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.824
Threshold uncertainty score0.889

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.307
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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