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Record W4410391326 · doi:10.1080/08865655.2025.2504888

Umbilical Object and Nostalgia in Chimamanda Adichie’s <i>Americanah</i>

2025· article· en· W4410391326 on OpenAlexvenueno aff
Mary J. N. Okolie, Onyekachi Obayi, Angel Adaugo Ik-Nwobodo

Bibliographic record

VenueJournal of Borderlands Studies · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicPostcolonial and Cultural Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsObject (grammar)ArtLiteratureLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

The psychological effect of migration can manifest as a feeling of homelessness, which goes beyond physical displacement to include emotional and cultural estrangement. The feeling of homelessness instigates a nostalgic yearning for home in the lives of immigrants and a longing for the familiarity of their homeland. Beyond this issue of unhomeliness and rootlessness, the psychological effect of migration also fosters resilience in the immigrant as individuals develop new coping mechanisms. Immigrants anchor on umbilical objects as a coping strategy to contain the psychological strain of migration. These umbilical objects are items, symbols, or practices, charged with significance and operate in a therapeutic and rejuvenating manner. Drawing on border theory, this study examines the experiences of immigrant characters moving across the border to foreign lands, their longing for home, and their attempts at reinvention through “umbilical objects’ as tokens of recuperation. Anchoring on Chimamanda Adichie’s Americanah, this paper interrogates the idea of home across borders. It explores how characters deploy umbilical objects to reinvent home in spaces of foreignness. Ultimately, this paper argues for the enduring significance of home and symbols of home in shaping the lives of immigrants.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0090.010
Scholarly communication0.0030.002
Open science0.0000.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.271
Teacher spread0.255 · 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 designNot applicable
Domainnot available
GenreOther

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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