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Record W2444602168 · doi:10.1080/08865655.2016.1174598

Chameleon Wall. Inside Two Competing Coalitions of Pro-“Fence” Actors in Israel

2016· article· en· W2444602168 on OpenAlexvenueno aff
Damien Simonneau

Bibliographic record

VenueJournal of Borderlands Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsnot available
FundersRégion Normandie
KeywordsFence (mathematics)NegotiationPoliticsPublic opinionPolitical sciencePolitical economyNorm (philosophy)PerceptionGovernment (linguistics)LawSociologyEngineeringPsychology

Abstract

fetched live from OpenAlex

Fourteen years after the start of the construction of the “security fence,” the idea of the West Bank Wall as a concrete separation from the Palestinians is a norm for the majority of the Israelis. The “security fence” represents a consensual security solution among the Israeli public opinion that is assumed to have stopped Palestinian attacks in Jewish-Israeli populated areas during the Second Intifada. This article explores the various meanings ascribed to the Wall by certain segments of Israeli society, specifically by pro-fence actors pressuring the Government between 2001 and 2005. Based on the identification of beliefs associated with the fence by such actors, the Wall appears to act as a Chameleon “solving” issues concerning security, identity, territory and separation. Beyond military and control purposes, the Wall also acts as a tool of reassurance on these issues to the Israeli public. The demonstration distinguishes between divergent and convergent meanings ascribed by pro-fence actors to the “security fence.” Nowadays, separation is favored over negotiations and territorial or political compromises. The Wall is thus a consensual public policy for most Israelis. It normalizes their daily life and perceptions of safety, and it moves them away from the Oslo period.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.743
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.059
GPT teacher head0.356
Teacher spread0.297 · 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 designObservational
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

Citations7
Published2016
Admission routes1
Has abstractyes

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