Bibliographic record
Abstract
Ta-Nehisi Coates’ book Between the World and Me is written as a letter to his son, but serves many roles: a collection of personal experiences as an African American man, a history of black people’s exploitation and oppression in America, and advice for navigating the country and its historical, systematic, expansive and deeply embeddedd racism. Readers and critics have noted the pessimism of the work, as Coates writes pragmatically and coldly with no optimism about the potential to end the racist oppression of black Americans. This essay analyzes Coates’ rejection of hope by parsing through the audiences he addresses and the respective messages underlying his work. First, the essay considers how Coates urges readers to think critically about the hopeful narrative of the American Dream and see how it obscures the racism underlying and determining both white Americans’ economic, political and social successes, as well as the struggles and cyclic obstacles afflicting black American communities. Using literary analysis, the essay argues that Coates’ rebuke of the American dream is meant to be addressed towards white Americans, as they are more susceptible to accepting its tempting and convenient narrative. Coates provides his son and the black American community with a different critique of hope; he shows the futility of maintaining optimism about the achievement of racial equality when that outcome depends on their nation and white peers who demonstrate no interest in ending the racist structures and systems that privilege them. Coates’ argument is clarified in the essay by framing it as a form of literary theorist Lauren Berlant’s conception of cruel optimism. Ultimately, by exploring the nuance in Coates’ pessimistic work, the essay reveals how Coates’ rejection of hope is both an effective message in addressing his various audiences and a justified sentiment, particularly given the high cost of holding on to hope for black Americans.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.030 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.009 |
| 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".