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Record W2571496372 · doi:10.7575/aiac.alls.v.8n.1p.60

The Different Types of Ethnic Affiliation in M. G. Vassanji's No New Land

2017· article· en· W2571496372 on OpenAlexaboutno aff
Hussein Ali Abbas, Manimangai Mani, Wan Roselezam Wan Yahya, Hardev Kaur

Bibliographic record

VenueAdvances in Language and Literary Studies · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicPostcolonial and Cultural Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDeportationEthnic groupIndependence (probability theory)TanzaniaColonialismGender studiesTheme (computing)DecolonizationSociologyEthnologyGeographyHistoryImmigrationPolitical scienceAnthropologyLaw

Abstract

fetched live from OpenAlex

Establishing a sense of affiliation to ethnicity is one of the most controversial issues for people who are displaced in countries that are far away from their motherland. The colonisation of the British over Asia and Africa in the nineteenth century resulted in the mass movement of Indian workers from India to Africa. These workers were brought in to build railways that connected the British colonies in East Africa namely Kenya, Tanzania, and Uganda. While the arrival of the Indian workers is considered as a kind of colonial practice, but their deportation in the post-independence years is seen as a part of decolonization. These Indians were forced to leave Africa as they were blamed for being non supportive of the Africans who were then engaged in armed struggles against the British colonialists. This study is based on the lives of these deported Indians as depicted in the novel titled No New Land by M.G. Vassanji. M.G. Vassanji is a Canadian novelist whose family was also deported from Dar Esslaam, Tanzania. He also describes how the Indian Shamses were strict in affiliating with the different social and cultural background they found in their new home, Canada. This research examines the theme of affiliation and the experiences of these migrants. This study will show that South Asians in Canada are strict in their affiliation to their ethnic values. Secondly, it will expose the three types of affiliation and finally show how the author deals with affiliation as a part of the community’s ethnic record that must be documented.

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: Empirical
Teacher disagreement score0.550
Threshold uncertainty score0.861

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 communication0.0000.001
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 head0.027
GPT teacher head0.313
Teacher spread0.286 · 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
Published2017
Admission routes1
Has abstractyes

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