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Record W2975902286 · doi:10.1080/13623699.2019.1666520

Occupation, settlement, and the social determinants of health for West Bank Palestinians

2019· review· en· W2975902286 on OpenAlexaff
Khalid Fahoum, Izzeldin Abuelaish

Bibliographic record

VenueMedicine Conflict & Survival · 2019
Typereview
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsPublic Health OntarioUniversity of TorontoMcMaster University
Fundersnot available
KeywordsWest bankSettlement (finance)Human settlementAppropriationSocial determinants of healthDemolitionPolitical sciencePoliticsHealth carePalestineEconomic growthDevelopment economicsGeographyBusinessEconomicsHistoryArchaeologyFinanceLaw

Abstract

fetched live from OpenAlex

A contentious issue in the Israel-Palestine conflict is the ongoing construction of settlements in the occupied West Bank along with its related policies, both of which have had impacts on the lives of resident Palestinians. These impacts have been documented by various UN and non-governmental agencies yet have been insufficiently studied in the academic literature. This article aims to review the literature on the social determinants of health for West Bank Palestinians and understand how settlement construction and policy influence these determinants. To accomplish these aims, the article first includes an analysis of how military infrastructure, resource allocation, land appropriation and house demolition related to the settlements influence the lives of West Bank Palestinians. The article then proceeds to review available literature on the social determinants of health in the West Bank, most notably: access to healthcare, exposure to political violence, economic conditions and water contamination, with the goal of understanding how settlement-related policies are related to these social determinants of health.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.952
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.505
GPT teacher head0.580
Teacher spread0.075 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations28
Published2019
Admission routes1
Has abstractyes

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