A Comparative Analysis of Black Racial Group Consciousness in the United States and Britain
Bibliographic record
Abstract
Abstract Extant scholarship on black politics has demonstrated the mobilizing effect that racial group consciousness can have on African American political participation. Few studies, however, test for or compare the political impact of group consciousness across national contexts. This paper presents an empirical comparison of group consciousness and its relationship with political behavior among black Americans and black Britons. Mobilizing two nationally representative surveys from the United States and Britain and a multi-dimensional measure of group consciousness, the findings presented here suggest that while elements of racial group consciousness are present among blacks in both societies, racial group consciousness is generally more prevalent and politically significant among blacks in the United States. For example, blacks in Britain are less likely to view blacks as occupying a fundamentally marginalized structural position and less likely to endorse race specific interventions that might address that marginalization. Results from regression analysis further suggest that while strong racial (rather than national) group attachment negatively affects the likelihood that blacks will vote in both countries, other elements of group consciousness are more strongly associated with participation among blacks in the United States than in Britain.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".