Schirin Amir-Moazami on the Epistemic Violence of Integration Politics in the Liberal-Secular Matrix
Bibliographic record
Abstract
In Interrogating Muslims: The Liberal-Secular Matrix of Integration ( 2022), Schirin Amir-Moazami brilliantly upends the continuing salience and pervasiveness of the so-called "Muslim Question" (MQ) in the North Atlantic world, with attention to its attending support for liberalism and secularism.Centered on contemporary Germany, over seven chapters, Amir-Moazami asks three primary questions: What is at stake with the imagined-as-urgent governmental work of integration, which Amir-Moazami shows works to manage religious diversity?What is expected of minorities in "successful" integration?And, why are minorities recurringly framed by a narrow and pejoratively framed Islam?In responding to these questions, Amir-Moazami de-naturalizes integration as a good or neutral goal of governance.On the contrary, she shows how the MQ obscures a contested terrain of majority/minority relations and identities.Given that I have few critiques of this very smart book, in what follows I outline what I see as its contributions and how I have recently mobilized its insights in my own work.Amir-Moazami engages and interrogates us/them binaries that undergird a liberal-secular matrix laden in the MQ.In her words, "The speech act that turns Muslims into potentially problematic and testable objects simultaneously constitutes a community of civilized and loyal citizens, who are paradoxically both abstract (liberal democratic) and concrete (native Germans)" (p.123).These
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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 | 0.000 | 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) | 0.000 | 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".