Humor and Identity in Elie Wiesel’s <i>Day</i> and Mordecai Richler’s <i>The Apprenticeship of Duddy Kravitz</i>
Bibliographic record
Abstract
Drawing on various theories regarding humor such as Freud’s analysis and the incongruity theory of humor, this essay will explore the humor in Elie Wiesel’s Day and Mordecai Richler’s The Apprenticeship of Duddy Kravitz, along with the conundrum of identity involved in this type of treatment. It analyzes the deployment of humor that appears in Day such as the “incongruity theory of humor”, the logic of the illogical, the “return of the physical into the metaphysical”, and the unique type of humor that Gyula represents, the implication of that humor and the consequent dungeon of the self that Eliezer is sentenced into. The essay then argues that Duddy, in his restless chasing of his goal, represents to some extent an escape from the humors of self-deprecation and self-punishment that characterizes the Jewish literature, and the dungeon of the self in which Eliezer in Day is caught, but is still portrayed as entangled in the Canadian-Jewish-Quebecois set of codes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.030 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".