Race as a Cause for Discrimination and “Othering”, Bernard Malamud’s The Tenants a Case Study
Bibliographic record
Abstract
The notion of discrimination and Othering acted upon people with different religious belief or race is as old as the human race itself. But the fact is that in modern times science even fueled the problem by presenting human hierarchy and the idea of superiority or inferiority of one race over the other. As a social phenomenon this issue entered into the realm of literary studies after it had been overtly or covertly used in literary works to foreground the problem. Bernard Malamud’s The Tenants deals with the conflict between two minority groups, Blacks and Jews, in American society. Emphasizing on the fact that physical features and religious belief are reasons for being treated as Other even in the most liberal society, Malamud indicates that the world has never been a Utopia and advances in science and technology did not eliminate racism and discrimination from society but they helped them change from one form to another.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.019 | 0.017 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".