The Fifty-Fifty Man: Understanding Diaspora through Indo-Canadian Literature
Bibliographic record
Abstract
Indo-Canadian Diasporic literatures deal with the displacement of identities and the cultural assimilation that occurs over generation and with re-discovering the ‘hyphenated-identities’ that forms a major part of a diaspora. The constant conflict between ‘homeland’ and the ‘host-land’ creates a feeling of displacement that becomes a central theme for diasporic literatures. Indo-Canadian diasporic people bond over their shared nostalgia of the homeland – they experience a sort of parallel existence with one foot in the homeland and the other in the host-land. Through the two prominent novels of Indo-Canadian diaspora – Anita Rau Badami’s Can You Hear The Nightbird Call? And Rohinton Mistry’s A Fine Balance we understand the diasporic identity and what it entails. We will study how the characters in both the novels are all effected by the socio-political and economic conditions of India during the 1975 Emergency and how it alters each character. Badami’s novel moves between the Sikhs living in India and Sikhs living in Canada and the plight of them, while Mistry deals with Hindu - Muslim conflicts. This paper focuses on how reading these Canadian literatures during a worldwide Covid-19 pandemic changes one’s understanding of diasporic literature, cultures and diasporic identities. In a covid-19 pandemic situation when many Indians living in Canada are horrified about the conditions in their homeland, their helplessness for not being able to visit, relying on virtual world/online modes of communication to keep themselves up to date on the conditions in their homeland. Reading Canadian literatures with historical contexts of crises, mass deaths, economic and sociological downfall, political crisis etc., at a time when we ourselves are undergoing or rather surviving through a worldwide pandemic with countless deaths, economic downfall etc., shapes or alters the approach towards diasporic literatures giving us a better understanding of Canadian literatures.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.051 | 0.035 |
| Scholarly communication | 0.017 | 0.006 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".