What Is a White Epistemology in Psychological Science? A Critical Race-Theoretical Analysis
Bibliographic record
Abstract
Critical race theory guides the analysis of the nature of a white epistemology in psychological science, the consequences for the study of race, and how scientific racism has been possible in the pursuit of knowledge. The article argues that race has not only been misused in the politics of psychology but misappropriated because of the logic of psychological science. The epistemic process is divided into four components to argue that naïve empiricist approaches in psychology, centered on scientific method, prevent an intricate understanding of race. Reasons for privileging method in psychology and the consequences of a white epistemology are discussed, including a narrow epistemic horizon and an inability to account for the temporality and contextuality of psychological phenomena. Ignorance, failure, or unwillingness to account for epistemic complexity when studying race are identified as problems. Questions about who benefits from narrow epistemologies are answered and suggestions for a broader practice of knowledge and education are provided.
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 | 0.021 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.011 | 0.070 |
| Scholarly communication | 0.013 | 0.021 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.007 |
| 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".