‘Class and “Race”. . . the two antinomic poles of a permanent dialectic’: Racialization, racism and resistance in Japan
Bibliographic record
Abstract
Despite the pervasive social constructivist turn, regardless of some exceptions, discussions of race, racialization and racism continue to focus on the relatively essentialist White/non-White binary. In this article, I move from the White/non-White binary to consider the dynamics and practices of racialization, racism and racial conflicts in Japan where there are no phenotypical distinctions between the dominant and the main racialized minority groups – the Burakumin , the Ainu , the Okinawans, the Zainichi Koreans and the Chinese. The main argument made in this article is that in Japan, class and power inequalities generated by colonialism, the division of labour, adoption and the deployment of the dominant Western 19th-century discourse of ‘scientific racism’ contributed to ‘racial formations’, ‘racial projects’ and the construction of the racialized boundaries that fuelled and continue to compete over material and non-material resources. A historical sociology of the permanent dialectic between class and race in Japan is offered in this article.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.026 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".