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Record W7128546327 · doi:10.64903/1480-6800-25.1.1

Jordan Valley Under Israeli Ihtilal: A Palestinian Story of Stark Oppression

2022· article· W7128546327 on OpenAlexvenueno aff
Ghazi-Walid Falah, Salwa Massad, Lina Adwan

Bibliographic record

VenueArab world geographer · 2022
Typearticle
Language
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOppressionPovertyJudaismIndigenousEthnic groupPopulationState (computer science)Fencing

Abstract

fetched live from OpenAlex

The Jordan Valley of Palestine is a site of poverty and targeting of a population, subjecting the native Palestinian inhabitants to sub-standard living conditions worse than any other areas in the West Bank under Israeli military occupation for more than half a century. Taking a grounded theory approach, this paper aims at presenting the voices of marginalized ordinary Palestinian locals, to be heard and reflected upon within a critical analytical geography context. For its part, Israel’s strategies of occupation and colonizing are geared towards controlling and fencing in over 90 percent of the Jordan Valley’s land, and by extension securing its resources (i.e., water, fertile agricultural and pastureland) for the benefit of the incoming Jewish settlers, now numbering some 10 000. This is at the expense of the indigenous 60 000 Palestinians, whose daily lives are marked by a severe lack of the adequate basics in health, access to education and other facilities, let alone minimum human rights. The paper details the daily life of Palestinians in the Occupied Jordan Valley, embedded within a system of oppressive actions and suffering inflicted on a population by a state prioritizing one minority ethnic group in the area over its natives. A critical geographic lens reveals the stark details of the Jordan Valley’s Palestinian social and spatial reality.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.573
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.277
Teacher spread0.248 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

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