Ethnic Identity and Cultural Assimilation in M. G. Vassanji’s No New Land
Bibliographic record
Abstract
Colonialism makes a large set of people from South Asia migrate to Africa. People from India are used as a man power for railway line construction in Africa. After the end of colonialism, these migrated people became competitors to Africans in employment. Africans start treating them harshly. So, they are forced to migrate once again to America or to Canada. M. G. Vassanji’s No New Land starts with the second migration of people from South Asia to Canada. Because of this second migration, these people want to make sure their connection to their culture and to their ethnicity. Their apartment in Canada looks like a mini version of Dar es Salaam. They try to stick to their Indianness in the midst of a completely strange culture. However, their kids who do not have any immediate connection with their culture start assimilating the new culture and way of living. This paper aims at projecting the plight of South Asian immigrants in Canada.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.009 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".