Bibliographic record
Abstract
Highlighting intersections between religion, culture, and race, Modood and Sealey propose the laudable ideal of a “multicultural secularism,” encompassed within a wider, diversity-affirming “multicultural nationalism.” Supporting this analysis, I argue that, in the current context, any account of secularism must thematize anti-Muslim bigotry. I illustrate my argument with examples from Canada and India, examining Islamophobia through scholarship in critical philosophy of race. The situations of racialized and non-racialized minority immigrant groups in Canada are different, a point not reflected in Canadian multicultural theories. In Quebec, Muslim women face unjustifiable restrictions on hijab, under the aegis of a secularism that functions as a mask for racism. India, for its part, has never been as pluralistic as the secular ideals within its constitution suggest. It also needs a “thickening” of identity, including the elements of de-othering and positive recognition that Modood and Sealey recommend as essential to genuinely multicultural nationhood.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".