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Record W2264705699 · doi:10.14452/mr-067-09-2016-02_5

Clerics and Communists

2016· article· en· W2264705699 on OpenAlexaboutno aff
Bashir Saade

Bibliographic record

VenueMonthly Review · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMiddle East Politics and Society
Canadian institutionsnot available
Fundersnot available
KeywordsCommunismPoliticsLeft-wing politicsIslamSpectacleHistoryDebtPolitical scienceEconomic historyMedia studiesReligious studiesHumanitiesClassicsSociologyLawArtPhilosophyArchaeology

Abstract

fetched live from OpenAlex

<div class="bookreview">Rula Jurdi Abisaab and Malek Abisaab, <em>The Shi'ites of Lebanon: Modernism, Communism, and Hizbullah's Islamists</em> (Syracuse, NY: Syracuse University Press, 2014), 350 pages, $49.95, hardcover.</div>In the West today, political Islam is mostly equated with ISIS's spectacle of violence, and with the narrow, bigoted understanding of religion and society that inspires it. It will thus intrigue many readers to discover that the legacy of Islamic intellectual and political activity, from the turn of the twentieth century until today, bore the imprint of a complex interaction between Communist and leftist traditions. A recent book by two professors at McGill University, Rula Jurdi Abisaab and Malek Abisaab, takes on the ambitious task of tracing the history of the sometimes symbiotic, sometimes confrontational relationship among Shi'i communities and clerics in Lebanon, along with occasional discussions of related issues in Iraqi politics. Based on a rich set of primary documents from both countries, the authors describe in great detail the rise and fall of the Communist experience in the region, the shortcomings of the left as it was gradually superseded by Islamic party formations, and the deep debt of the latter to the former.<p class="mrlink"><p class="mrpurchaselink"><a href="http://monthlyreview.org/index/volume-67-number-9" title="Vol. 67, No. 9: February 2016" target="_self">Click here to purchase a PDF version of this article at the <em>Monthly Review</em> website.</a></p>

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: Review · Consensus signal: Review
Teacher disagreement score0.954
Threshold uncertainty score0.187

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 head0.034
GPT teacher head0.323
Teacher spread0.289 · 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
GenreReview

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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