TODD VOGEL. ReWriting White: Race, Class, and Cultural Capital in Nineteenth-Century America. New Brunswick: Rutgers University Press. 2004. Pp. x, 194. $22.95
Bibliographic record
Abstract
Audre Lorde famously wrote that the master's tools would never dismantle the master's house. In this book, Todd Vogel demonstrates how a careful rereading of American cultural and intellectual history complicates, if not completely contradicts, Lorde's pronouncement. Taking Standard English as one of the principal instruments in the master's toolbox, Vogel argues that appropriating “‘white’ language to write about nonwhite experience”—what he calls the “supplanter tactic” (p. 10)—was one of three strategies nineteenth-century minority authors, actors, editors, and orators used to subvert and otherwise dismantle dominant discourses of whiteness and regnant ideologies of white superiority. Although there is considerable overlap among them, the other insurrectionist tactics Vogel identifies are what he calls “revisionist narration,” the purposeful refiguring of foundational myths of national origin, and “social theory,” the direct engagement with and challenge to “white aesthetics,” which people of color used to rewrite, “again in ‘white’ language,” prevailing definitions of race and gender (p. 10).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".