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Record W3098136968 · doi:10.37867/te120201

A COCOON IN A FOREIGN LAND: VASSANJI’S SHORT FICTION

2020· article· en· W3098136968 on OpenAlexaboutno aff
Aditi Vahia

Bibliographic record

VenueTowards Excellence · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicPostcolonial and Cultural Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIndependence (probability theory)HindiPoliticsInnocenceHistoryIdentity (music)HomelandSociologyPolitical scienceGeographyGender studiesGenealogyLawArtAesthetics

Abstract

fetched live from OpenAlex

In the ‘Foreword’ to his collection Uhuru Street, Vassanji observes that ‘Uhuru’ means ‘independence’. The Kichwele Street of Dar es Salaam – later renamed as Uhuru street nurtures the spirit of independence irrespective of the continual changes that the street experienced from the sheltered innocence of colonial rule in the 1950s to the shattered world of the 1980s. This collection of short stories – as many of Vassanji’s works is characterized by “a complex ethno-cultural identity” that incorporates multiple countries (Kenya, Tanzania, India, Canada, U.S.A.), religions (crucially, the syncretic bhakti tradition he was raised in), languages (Gujarati, English, Swahili, Hindi). , The stories in Uhuru Street explore political and social change in the city of Dar es Salaam in the East African country of Tanganyika. They follow a historical arc which begins in the years leading up to independence (in 1961) and concludes in the decade or so. This paper analyzes the microcosm of an immigrant world as portrayed by Vassanji in his Uhuru Street through its eccentric characters giving us a portrait of a place and a people losing their innocence. The stories come together as a story of generations new and old, the former searching for a new identity, the latter, fiercely holding onto the past. We share with these people the moment of moving on, of leaving the place where we have roots, knowing that things will never be the same.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.859
Threshold uncertainty score0.810

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.061
GPT teacher head0.236
Teacher spread0.176 · 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 designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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