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
W. E. B. Du Bois is credited with debunking the social Darwinism pervasive in turn-of-the-century social and political theory, exposing the environmental causes of black disadvantage and undercutting claims regarding “inborn” racial deficits. This, however, misses the constructive role that Darwinism played in his account of racial advancement. This article shows how Darwinism, eugenics, and race science shaped Du Bois’s conceptualizations of race and of racial uplift. Darwinism, I argue, informed his analysis of the harms that slavery and segregation visited on black Americans. It also influenced his defense of democratic equality: setting aside its other virtues, democracy would remove “artificial” constraints on the competitive struggle, enabling the best of white and black races to succeed. It was, then, eugenically advantageous. Against the common view that Du Bois rejected social Darwinism and eugenics, I demonstrate that their relationship was far more ambivalent and that his racial politics appealed to them.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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