BEYOND “FIXED” AND “MIXED” RACIAL PARADIGMS: THE DISCURSIVE PRODUCTION OF THE HISPANIC AND THE 2000 U.S. CENSUS
Bibliographic record
Abstract
"This essay juxtaposes the proliferation of discourse on and about the Hispanic in the wake of the 2000 U.S. Census with performative representations of American cultural identity by Mexican-Chicano Guillermo Gómez-Peña and Native Canadian Monique Mojíca. In opposition to the new multiracialism of the 2000 U.S. Census, both anti-racist critical theorists of whiteness and conservative anti-Hispanic analysts decry the loss of a binary racial paradigm that clearly defines Euro-American culture against its non-English-speaking others. These theorists mistakenly blame multiracialism—and the Hispanics who define themselves in this distinct register—as a problematic threat to a one-drop racial paradigm, based on notions of racial purity. By contrast, multilingual, trans-American representations in Gómez-Peña and Mojíca look beyond the false dilemma of mixed and fixed racial paradigms in order to criticize the assimilationist legacies of European coloniality. They comparatively reconstruct the traumatic history of mestizaje in order to envision alternative representations and distinct futures for the Americas."
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".