Bibliographic record
Abstract
For many Black girls, the realization that the world was not designed for them to flourish mars their childhood. My presentation discusses how society fails Black girls, and how Morrison’s fictional writing mirrors how unforgiving life is to real Black children. Throughout the novel, the narrator Claudia uses “magical thinking” to explain the world’s cruelty. This manifests when she plants marigolds, childishly hoping their flourishing will simultaneously save Pecola and her baby (Morrison). Claudia believes in magic because the reality is incomprehensible for a child: that the idealization of whiteness ingrained in society created a soil in which neither marigolds nor Pecola could thrive. Similarly, she naively dismembers her "Shirley Temple" doll to discover the source of the “magic” that whiteness casts over her world (Morrison). Her belief in magic is easier than accepting the world values white plastic faces over living blackness. I hope to demonstrate that Morrison’s novel goes beyond fiction: it encapsulates children’s perspectives and how they mature. Children live in fiction, an imaginary world of their creation, and childhood is the moment before they realize the weight of society. For Claudia, Pecola, and many Black girls, the heaviness of realizing their world will ostracize and hurt them is growing up, there is nothing magical about adulthood. For a novel from 1970, The Bluest Eye is still relevant because we continuously rob Black girls’ innocence. Morrison presents an unconventional depiction of childhood, and my presentation reaches above to discuss how fiction reflects the real ways society disrupts Black girlhood.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.017 | 0.009 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.038 | 0.005 |
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".