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Record W4323921722 · doi:10.1111/aman.13823

Gucci and the waqf: Inalienability in Beirut's postwar reconstruction

2023· article· en· W4323921722 on OpenAlexaff
Nada Moumtaz

Bibliographic record

VenueAmerican Anthropologist · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMiddle East Politics and Society
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCapitalismEndowmentExpropriationWaqfValue (mathematics)Private propertyPolitical scienceLawSociologyHistoryIslamArchaeology

Abstract

fetched live from OpenAlex

Abstract On August 4, 2020, one of the largest nonnuclear explosions in history rocked the city of Beirut, leaving over 200 people dead, 6,500 injured, and 300,000 homeless. As Beirutis debated strategies for rebuilding, another reconstruction project haunted their discussions: the postwar reconstruction of Beirut's city center, overseen by the private company Solidere. For many, Solidere stands for a neoliberal reconstruction project that placed profits over people, expropriating rights‐holders for company shares. While most organizing against Solidere in the 1990s failed, this article turns to a little‐known but more‐successful mobilization involving Solidere's expropriation of parcels and buildings that had been endowed as inalienable Islamic trusts. Many Beiruti Muslims rallied against these expropriations, citing endowment inalienability and resulting in publicized recuperations. Yet, archival and ethnographic research shows that this mobilization led to the recuperation of only some of these endowed properties. Many others were taken to market in order to allow for the perpetuation of the few. This chapter in the reconstruction of Beirut's city center complicates our understanding of capitalism, alienability, and inalienability, illustrating both the constant work needed to create free markets and the continued effectiveness of discourses of inalienability that perpetuate other forms of value and property under capitalism.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.860
Threshold uncertainty score0.954

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.081
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 head0.018
GPT teacher head0.347
Teacher spread0.329 · 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.

Study designQualitative
Domainnot available
GenreEmpirical

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

Citations1
Published2023
Admission routes1
Has abstractyes

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