Secularism versus Awkwardness in Public Spaces: An Online Ethnography with Muslims in Windsor, Ontario
Bibliographic record
Abstract
This dissertation asks how Muslims in Windsor, ON imagine and undertake political action, often formed through the lived experiences of migration, gender, and class, in the context of Canadian secularism. I argue that secularism has the neo-colonial effect of oppressing marginalized peoples by excluding them from public spaces and undermining democratic engagements. However, as my fieldwork exposed secularism’s tacit discriminatory effects, it also revealed how Muslims thrive despite restrictions on their public lives, resist oppression, and create open communities where everyone willing to learn is welcome. Theoretical engagements with the works of Hannah Arendt and Sara Ahmed reveal that Muslim political action works by learning with and from each other about Islamic life in a western society. These learnings ground them in Islamic tenets while at the same time provide them with histories, cultures, and literary works pertaining to their own peoples which, in turn, allows them to analyze life in Canada as it pertains to their positionality. I add to theories of action by showing how BIPOC ways of being with and learning about their positionality is not only a way of preservation, but also a way of democratic engagement. Ultimately, by means of affect theory, I argue that awkwardness offers a key moment of possibility for democratic engagement between Muslims and non-Muslims. Online ethnography was the most effective means to access the Muslim community in Windsor, Ontario because their lives, like most people’s, were online during the pandemic, a fact that merely intensified prior lived reality rather than deviated from it. Without online research especially during the pandemic, marginalized groups would be at risk of under-representation, either from the impact of Covid or from other areas of vulnerability such as Islamophobic events. The research draws on extended, unstructured interviews with 27 participants, participant-observation in online settings, and on social media as well as on current events, news, and policies as they pertain to Muslims in Canada.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.011 |
| Scholarly communication | 0.004 | 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".