Defining Whiteness: Race, Class, and Gender Perspectives in North American History
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
African-American writers such as W. E. B. Du Bois, James Baldwin, and Ida B. Wells have regarded “whiteness” as a problem for a long time. However, it is only fairly recently that white historians have taken seriously the importance of de-naturalizing “whiteness,” and critically examining its privileges. “Defining Whiteness: Race, Class, and Gender Perspectives in North American History,” was sponsored by the University of Toronto and York History Departments, the Centre for the Study of the United States, and the Centre for Ethnic and Pluralism Studies at the University of Toronto, with the cooperation of International Labor and Working-Class History and the Canadian Committee on Labour History and its journal Labour/Le Travail. Conference organizers invited several leading American scholars of “whiteness” to Toronto, where they, along with a number of Canadian scholars, presented papers on the ways that whiteness has been constructed in North America. The conference contained much to interest labor historians and those interested in class/race/gender analytical frameworks.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it