“A child isn’t born bitter”: (In)human Relations and Monstrous Affects in Hiromi Goto’s The Kappa Child
Bibliographic record
Abstract
This article presents an intersectional reading of Hiromi Goto’s The Kappa Child (2001) through the lens of Affect Theory. Particularly, I draw from Sara Ahmed’s The Promise of Happiness and Lauren Berlant’s Cruel Optimism to analyze the role these notions play in the novel. I focus on the economy of affects that circulates among the characters and the affective significance of their interactions as well as the novel’s engagement with Ahmed’s notion of the promise of happiness and Berlant’s cruel optimism, specifically in relation to female, racialized, and migrant subjects both at a personal level and in the context of the settler colonial nation. My main argument is that the affects and expectations presented in the novel are monstrous. I defend that the protagonist’s affective monstrosity is a direct consequence of her abusive childhood as a racialized migrant in the Canadian Prairies and that choosing to let go of her expectations leads to emotional healing and opens new possibilities towards happiness.
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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 | 0.021 | 0.026 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| 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".