Unveiling Whiteness in the Twenty-First Century
Bibliographic record
Abstract
Unveiling Whiteness in the Twenty-First Century: Global Manifestations, Transdisciplinary Interventions is a tightly interconnected and richly collaborative book that will advance our understanding of why it is so difficult to re-form and reimagine whiteness in the twenty-first century. Composed after the election of the first black U.S. president, post-global financial crisis, more than a decade after 9/11, and concomitant with a rash of xenophobic incidents across the globe, the book distills several key themes associated with a post-millennial global whiteness: the individual and collective emotions of whiteness, the recentering of whiteness through governing and legal strategies, and the retreats from social equity and justice that have characterized the late twentieth and twenty-first century nation state. It also attempts the difficult work of reimagining white identities and cultures for a new era. Chapters in Unveiling Whiteness in the Twenty-First Century draw from the fields of African-American studies, English studies, media studies, philosophy, political science, psychology, sociology, education, and women’s studies. Using transdisciplinarity as a mode of inquiry for the project and responding to the changing phenomenon of whiteness across several continents (Australia, Canada, France, Romania, South Africa, Sweden, and the United States), the collection brings together established and emerging scholars and a range of critical approaches to unveil and intervene in the ideologies of whiteness in our contemporary moment. Unveiling Whiteness in the Twenty-First Century demonstrates that complex inquiry and activism are needed to challenge new iterations of whiteness in twenty-first-century political and social spaces.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.026 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".