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Record W4417400309 · doi:10.1163/09763457-bja10198

Re-Imagining Home in Transnational Narratives

2025· article· W4417400309 on OpenAlexaff
Reza Ashouri Talooki

Bibliographic record

VenueDiaspora Studies · 2025
Typearticle
Language
FieldSocial Sciences
TopicDiaspora, migration, transnational identity
Canadian institutionsKeyano College
Fundersnot available
KeywordsDiasporaEmbodied cognitionScholarshipNarrativeEveryday lifeNegotiationRelation (database)Politics

Abstract

fetched live from OpenAlex

Abstract This article analyses Firoozeh Dumas’s memoirs, Funny in Farsi and Laughing Without an Accent , to examine how Iranian-American homemaking is constructed as a dynamic, embodied and sensory process in diaspora life writing. Drawing on recent scholarship in diaspora studies, the sociology of home and life writing, the article introduces and develops the concept of ‘multisensory homing’ as an innovative interdisciplinary framework. This approach theorises diasporic belonging as materially constituted through everyday embodied practices—tasting, smelling, laughing—that go beyond symbolic or nostalgic models of home and extend existing spatial and temporal paradigms by centring humour and affective materiality. The discussion situates Dumas’s work in relation to classic and recent diaspora theory as well as Iranian-American humour and life writing, highlighting its distinctive intervention: a sensorially grounded focus on everyday resilience and cultural negotiation as an alternative to trauma-centric or political accounts, offering new insight into the relational practice of homemaking for migrants and minorities across contemporary transnational contexts.

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)0.006
metaresearch head score (Gemma)0.008
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 score0.010
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0080.024
Scholarly communication0.0100.016
Open science0.0010.010
Research integrity0.0020.003
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 head0.049
GPT teacher head0.375
Teacher spread0.325 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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