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Record W7128538581 · doi:10.64903/1480-6800-27.1.1

The Geopolitics of Israel's “Seam Zone” in the West Bank of Palestine

2024· article· W7128538581 on OpenAlexvenueno aff
Ghazi-Walid Falah, Samer Al-Nawaiseh

Bibliographic record

VenueArab world geographer · 2024
Typearticle
Language
FieldSocial Sciences
TopicAgricultural and Environmental Management
Canadian institutionsnot available
Fundersnot available
KeywordsGeopoliticsWest bankSovereigntySettlement (finance)Sovereign stateDeclarationState (computer science)Palestine

Abstract

fetched live from OpenAlex

This paper discusses how Israel has intensified its settlement activities in areas immediately east of the 1949 Armistice Line/Green Line, seeking to carve out 13% of West Bank territory and add this to its pre-June 1967 sovereign space. In doing so, state planners have engineered the Separation Wall (SW), an 8-meter-high barrier in part and twice as long as the Green Line. This Wall is designed to ‘border and order’ territories that Israel desires to annex, declaring it as a Seam Zone (SZ), since it lies between the Separation Wall and the Green Line. Concomitant with these colonial activities, Israel has imposed a strict system of military control on Palestinian communities. While some such communities were conditionally left inside the SZ and are living in their localities upon presenting proof of permanent residency, many others were arbitrarily separated by the SW from their best fertile land and water resources. This unilateral step in settlement implementation aims to further Israel's geopolitical strategy of creating ‘facts on the ground.’ The now imminent declaration of the SZ as Israeli sovereign space was backed up by Trump's Deal of the Century (DoC) announced in January 2020. In 2024 the SZ remains an open question.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.011
GPT teacher head0.240
Teacher spread0.229 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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