The Subject of Multiculturalism:
Bibliographic record
Abstract
Contemporary political theory debates about multiculturalism largely take for granted that it is “culture ” and “cultural groups ” that are to be recognized and accommodated. Yet, the discussion tends to draw on a wide range of examples involving religion, language, ethnicity, nationality, and race. Culture is a notoriously overbroad concept, and all of these categories have been subsumed by or taken to be synonymous with the concept of culture. Consider some prominent examples. In Charles Taylor’s account, culture is understood primarily in terms of language. Each language is taken to be the expression of the authentic identity of a Volk. The culture of Quebec, Taylor says, “means in practice the French language.”1 Beyond language, the ‘politics of recognition ’ that Taylor explores in his seminal essay seems to encompass not only claims by ethnic and national minorities but also by women and racial minorities for the recognition of the equal worth of their collective identities.2 The attempts by American educators in the 1970s, 80s, and 90s to include the cultural contributions of Native Americans, African Americans, and Asian Americans in school curricula is one prominent example.
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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 | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.062 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.006 | 0.009 |
| 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".