What Blood Won't Tell: A History of Race on Trial in America. By Ariela J. Gross. (Cambridge: Harvard University Press, 2008. xii, 368 pp. $29.95, ISBN 978-0-674-03130-2.)
Bibliographic record
Abstract
In 1790, absent any explicit federal definition of citizenship, Congress restricted eligibility for naturalization to “any alien, being a free white person.” In 1952 the racial requirement was revoked. During the intervening 160 years, race and citizenship became mutually constitutive categories in American culture, as Ariela J. Gross demonstrates in her delightfully readable legal history of racial identity in the United States. The persistent inextricability of race and citizenship leads Gross to reject one strand of the history of race in the United States, the rise of the so-called one-drop rule (p. 297), as well as to call into legal-historical question claims made by whiteness studies scholars about the perceived racial alterity of immigrant groups such as the Irish and Italians. Reviewing freedom suits, miscegenation trials, naturalization cases, and myriad other proceedings, Gross persuasively exposes the shifting sands upon which the unstable but formidable (and enduring) edifice of race in America has been built. In her account, “blood” has seldom, if ever, been the sole juridical criterion for race. Rather, Gross argues, early efforts to locate race in appearance and ancestry were superseded by increased attention to civic performance, local reputation, and personal association in the nineteenth century, followed in the twentieth and twenty-first centuries by heightened sensitivity to science, national citizenship, and cultural practice. Taking a wider view than classic histories of race by Winthrop D. Jordan and George Frederickson and deftly incorporating the theoretical insights of such legal scholars as Cheryl I. Harris and Devon W. Carbado, Gross's study is a worthy counterpart to Rogers M. Smith's magisterial analysis of the inegalitarian, ascriptive traditions of American citizenship, Civic Ideals (1997).
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.008 | 0.015 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".