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Record W4414384555 · doi:10.1080/0377919x.2025.2561121

Charting Cultural Territory: Imagined Geographies and Water Politics in the Works of Mahmoud Darwish

2025· article· en· W4414384555 on OpenAlexfundno aff

Bibliographic record

VenueJournal of Palestine Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council
KeywordsPoliticsCultural politicsIdentity politicsSubjectivityPerspective (graphical)Identity (music)

Abstract

fetched live from OpenAlex

This article reads water imagery in Mahmoud Darwish’s poetry as an example of cultural and geographical reclamation that refuses the orientalist discourse that writes Palestinians out of their land. It posits that this Western discourse functions through Zionist environmental apartheid, a system of injustice meant to further dispossess Palestinians of their lands and land-based identities. Situating this analysis within the ongoing genocide in Gaza and the rise in accusations of antisemitism against Palestine advocates, the author argues that the riverscapes and seascapes imagined within Darwish’s hydropoetry humanize and personify Palestine’s Jordan River and Mediterranean Sea. Read this way, the slogan “from the river to the sea, Palestine will be free” encompasses the rediscovery and recharting of these water bodies as sites and beings of active resistance, thus enabling the creation of alternative Palestinian futures.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0150.049
Scholarly communication0.0090.005
Open science0.0010.006
Research integrity0.0020.002
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 head0.034
GPT teacher head0.340
Teacher spread0.306 · 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 designQualitative
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

Citations2
Published2025
Admission routes1
Has abstractyes

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