Bibliographic record
Abstract
Julia Kristeva, the Bulgarian-French critic, claims that the melancholic subject has a sense of loss and s/he cannot share it with other people as s/he considers it private. S/ he is stranger to her/his mother tongue and cannot express her/his feeling through language; however, s/he should use language in order to get rid of her/his sense of loss. In The Bluest Eye, Toni Morrison devotes herself to the slaves' experience. She believes that the slaves suffer from their past and feel a sense of loss, and they should use language to express their feeling. This article intends to apply Julia Kristeva’s theory of the melancholic subject to Toni Morrison’s The Bluest Eye and shed light on the fact that through language the characters become able to deal with their past. Key words : Julia Kristeva; The melancholic subject; Toni Morrison; The Bluest Eye; Language; Loss
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.038 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 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".