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Record W4308566786 · doi:10.1163/18739865-01504005

Jawlān

2022· article· en· W4308566786 on OpenAlexaff
Aamer Ibraheem, Adrien Zakar

Bibliographic record

VenueMiddle East Journal of Culture and Communication · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMiddle East Politics and Society
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAutocracySovereigntyPoliticsState (computer science)IdeologySociologyScope (computer science)Political economyLawPolitical scienceMedia studiesDemocracy

Abstract

fetched live from OpenAlex

Abstract In this article, we focus on the keyword Jawlān to highlight one of the most critical, if overlooked, dimensions of autocracy in modern Syria. Occupied by Israel in 1967, the Jawlān is a borderland where words have made political relationships possible, sustaining forms of national and kin attachments for decades. We show how, within post-1967 Syria, the Jawlān came to function as a discursive vessel for the state to address its citizenry outside the boundaries of the Golan Heights. When the 2011 moment began, ways of communicating with the state were enacted to both buttress the autocracy and solidify the resistance movement opposing it. We offer an analysis demonstrating how these various ways of hailing had grown out of autocracy but came to frame communications among citizens and structure civic relations beyond the workings of the regime and the geographical scope of its sovereignty. Drawing on the dynamics in play at this moment, we contribute to current discussions on neoliberal autocracy and borderland ontologies, approaching ideological interpellation as a mode of enfolding diasporic Syria spaces and communities outside regime-controlled areas into its political order.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.550
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0050.004
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.5500.289

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 head0.044
GPT teacher head0.283
Teacher spread0.239 · 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 source (direct Gemma or distilled Codex), 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".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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