Contesting Power: A Comparison of Muslim Civil Society Responses to Counter-Radicalization Policies in Canada and the U.K.
Bibliographic record
Abstract
In the context of the 'war on terror,' counter-radicalization (CR) policies are a form of security governance that uses social, cultural, and educational programs to preempt the future possibility of political violence. Based on a problematic understanding of 'radicalization' as the transition toward 'extreme' Islamic ideology, CR policies have principally targeted Muslim communities. As Muslim civil society organizations (CSOs) are enlisted to support counter-radicalization objectives, they have to balance advocating for Muslim communities - including raising concerns about anti-Muslim discrimination in CR policies - on the one hand, and on the other, acceding to participate in counter-radicalization initiatives. Employing a qualitative comparative approach, my dissertation shows how Muslim CSOs in Canada and the U.K. develop strategic responses to CR policy pressures. Data for this research are based on interviews with decision-makers at Muslim CSOs, policymakers, and informed individuals as well as analysis of policy documents and security practices related to counter-radicalization. I propose a conceptual framework that integrates theorization of power (Haugaard, 2012, 2021) with an organizational institutionalist model (Oliver, 1991), arguing that CR polices create relations of power between state institutions and Muslim CSOs, and responses of Muslim CSOs are best understood as contestations within these relations of power. My analysis reveals that, despite following different patterns of development, CR policies in Canada and the U.K. govern Muslims through racialized practices and notions of the "suspect community," risk, and preemption. Through CR policies, state institutions seek to produce compliant CSOs that unreflexively reproduce relations of domination. With the awareness of these dynamics, Muslim CSOs engage in sophisticated power contestations: 1) they make strategic choices about availing CR-related funding, cooperating with state security institutions, and responding to state institutions' withholding legitimacy for CSO activities, 2) they criticize state institutions for insufficiently including Muslim CSOs in the CR policymaking process and for ignoring the concerns of Muslim communities, and 3) they challenge dominant discourses in CR policies and demand more transparency about the knowledge basis for CR policies. This dissertation shows how, despite institutional constraints, CSOs can use their agentic power to engage in meaningful contestations toward emancipatory goals.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.019 | 0.011 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".