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Record W4413210848 · doi:10.1080/08865655.2025.2539108

Dialectic of Un/Belonging in Emily Habiby’s <i>The Secret Life of Saeed, the Pessoptimist</i>

2025· article· en· W4413210848 on OpenAlexaffvenue
Sosthenes Nnamdi Ekeh, Mary J. N. Okolie

Bibliographic record

VenueJournal of Borderlands Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicMiddle East Politics and Society
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDialecticPhilosophyPsychoanalysisLiteratureEpistemologyPsychologyArt

Abstract

fetched live from OpenAlex

The Israeli-Palestinian border conflict has continued to shape discourse in border studies, playing up the various ramifications by which borders are legitimized and performed in contemporary times. This perennial conflict has also set the tenor of Arab literature, casting a distinguishing profile of literary expediency on the tradition. However, most border-focused criticisms of Arab literature, as well as the literary representation of the border issue, tend to overlook the complexity posed by the lived experience. Habiby’s The Pessoptimist situates itself within this complex dynamic of lived border experience, problematizing the question of belonging and unbelonging through the everyday realities of Saeed, the protagonist, and the Palestinian Arabs in the State of Israel. This research, therefore, draws insights from Nira Yuval-Davis’s theory of belonging to interrogate the dynamic experience of un/belonging, while paying attention to how the narrative foregrounds it as a dialectical mode of being. We argue that although the novel complicates the question of belonging and unbelonging, the analysis of Saeed's experience and that of other Palestinian Arabs reveals that these two existential situations are not so opposed, but can be understood dialectically as a mode of living following the divide created by the Israeli-Palestinian border conflict, which serves thereby as a new mode of belonging.

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)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.131
Threshold uncertainty score0.307

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.021
GPT teacher head0.324
Teacher spread0.303 · 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 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

Citations0
Published2025
Admission routes2
Has abstractyes

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