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Record W3203607870 · doi:10.3968/12208

Cultural Boundary and Ethnic Identity in A passage to India

2021· article· en· W3203607870 on OpenAlexvenueno aff
Jiansheng Yan

Bibliographic record

VenueCross-cultural communication · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicSouth Asian Studies and Diaspora
Canadian institutionsnot available
Fundersnot available
KeywordsEthnic groupCriticismGender studiesEthnocentrismCultural identityColonialismIdentity (music)OrientalismState (computer science)SociologyHistoryPolitical scienceAnthropologySocial scienceLawAestheticsArt

Abstract

fetched live from OpenAlex

Based on an Indian doctor Aziz’s experience in contact with the British people and the subsequent “Aziz’s Incidents”, A Passage to India reflects the cultural clash between the suzerain and the vassal state and the crisis of ethnic identity caused by cultural conflict during the colonial times in India. Obviously, the Indian “Cultural Other” was marginalized and repressed by the British “Culture itself” at that time, human weakness revealed once again attributed by ethnocentrism. After the novel was published, it once aroused strong repercussion from readers, academic circles such as Criticism of Orientalism was incessant, the author Foster was also pushed to the top of the critical wave and was acused constantly. In fact, study shows that Aziz’s story was both universal and symbolic, it was an inevitable result of the cultural boundary which existed between Britain and India during the colonial period, and this problem was the key factor for the unequal ethnic groups’ identity between British people and Indian people.

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)0.004
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0200.018
Scholarly communication0.0080.002
Open science0.0010.008
Research integrity0.0010.004
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 head0.057
GPT teacher head0.357
Teacher spread0.300 · 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
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
Published2021
Admission routes1
Has abstractyes

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