Bibliographic record
Abstract
Toni Morrison has long proposed that the concept of physical beauty is one of the most destructive ideologies of human thought. This essay aims to deal with how Morrison’s 1970 novel The Bluest Eye exposes the dogma that physical beauty and pureness itself are straightforwardly associated with whiteness; allowing whiteness to provide a cloak of invisibility to those who possess it. This then subjects blackness to be the placeholder of what is ugly, bad and dangerous in the world; forcing the trait of blackness to be a conviction of visibility. This essay will follow myself, a white individual, grappling with the fact that I have been given the privilege to go through life unnoticed only because I happened to be born white. Further, the repercussions of this fact are confronted, those who are black are stripped from the privilege of going unnoticed. The Bluest Eye and my mediation of the novel present that even a raised consciousness about the privileges of whiteness fails to prevent racial self-loathing and violence against Blacks due to whiteness taking over the measure of humanness. Despite this, there is still hope in the future of blackness which can only be accomplished by displacing the authority of whiteness and questioning the structures that allow the authority of whiteness to prevail.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.019 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".