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Record W1502950163

India via Trinidad and Canada: Negotiating Hospitality in Shani Mootoo’s Short Stories

2012· article· en· W1502950163 on OpenAlexaffvenueabout
Chandrima Chakraborty

Bibliographic record

VenueStudies in Canadian Literature · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicCaribbean history, culture, and politics
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDiasporaHospitalityNegotiationConsolidation (business)Gender studiesSociologyFace (sociological concept)Reading (process)Identity negotiationHistoryEthnic groupMedia studiesAnthropologyTourismPolitical scienceSocial science
DOInot available

Abstract

fetched live from OpenAlex

“Out on Main Street” and “The Upside-downness of the World as it Unfolds,” two stories from Shani Mootoo’s 1993 collection, explore how Canada functions as an interface between the Indian diaspora and its originary cultures. The stories play on dominant impulses to assign ethnic belonging based on skin colour, and Jacques Derrida’s reading of the contradictions inherent in (conditional) hospitality can help us tease out the implications of welcome offered to, and perceived by, Mootoo’s misread and racialized Indo-Trinidadian narrators. These stories illuminate how “India” travels from one diaspora (Trinidad) to another (Canada) and how face-to-face urban encounters enable the consolidation of “Indianness” in Canada. More specifically, they shed light on the processes through which diasporic Indians and white Canadians reproduce norms of Indianness and how these norms erase histories and distinctions within the broader Indian diaspora. Ultimately, Mootoo counters the way skin colour is “read” in Vancouver, and the asymmetries of intercultural encounter in these stories stress the need for a historicized and contextualized understanding of the multiplicity of Indian diasporas in Canada.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.645
Threshold uncertainty score0.873

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.025
GPT teacher head0.312
Teacher spread0.288 · 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 designObservational
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

Citations3
Published2012
Admission routes3
Has abstractyes

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