Bibliographic record
Abstract
In this article, we argue that, in order for white racial consciousness and practice to shift toward an antiracist praxis, a relational understanding of racism, the “self,” and society is necessary. We find that such understanding arises from a confluence of propositional, affective, and tacit forms of knowledge about racism and one's own situatedness within it. We consider the claims sociologists have made about transformations in racial consciousness, bringing sociological theories of racism into dialogue with research on whiteness and antiracism. We assert that sociological research on white racism and “whiteness” tends to privilege propositional and tacit/common sense knowledge, respectively, as critical to shifting white racial consciousness. Research on antiracism privileges affective knowledge as the source of antiracist change. We examine some of Perry's recent ethnographic research with white people who attended either multiracial or majority white high schools to argue that the confluence of these three types of knowledge is necessary to transform white racial praxis because it produces a relational understanding of self and “other,” and, by extension, race, racism, and antiracist practice.
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.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.028 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".