Race, Rhetoric, and Judicial Opinions: Missouri as a Case Study
Bibliographic record
Abstract
This Essay studies the relationship between race, rhetoric, and history in three twentieth century segregation cases: State ex rel. Gaines v. Canada, Kraemer v. Shelley, and Liddell v. Board of Education. Part I gives a brief overview of the scholarship of Critical Race Theory, majoritarian narratives and minority counter-narratives, and the judiciary’s rhetoric in race-based cases. Part II analyzes the narratives and language of Gaines, Kraemer, and Liddell, provides the social context of these cases, and traces their historical outcomes.\nThe Essay contends that majoritarian narratives with problematic themes continue to perpetuate even though court opinions have evolved to use less explicit race-based rhetoric. The Essay proposes that this rhetoric has been replaced with majoritarian enthymemes, i.e., unstated assumptions about race. These majoritarian enthymemes allow the underlying narratives of historic court opinions to retain vitality even outside of the courts. The Essay concludes that long-lasting societal change has been elusive, in part, because, without explicitly rebutting majoritarian narratives and giving voice to counter-narratives, even progressive judicial opinions cannot effectively challenge the status quo.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.022 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| 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".