Close Encounters Under the Muslim Ban: Mobile Media, Intimacy, and Augmented Whiteness
Bibliographic record
Abstract
This article examines how everyday mobile media produce discursive and affective modes of closeness that circulate as part of the Canada-US border-making process under the Muslim ban. I contend that although the #WelcomeToCanada hashtag, which was made popular by Justin Trudeau’s tweets in response to the US travel ban, presents an inclusive, multicultural Canada that appears to contrast the white supremacist, xenophobic narrative of Donald Trump’s executive order, its performance of flexible Canadian borders actually renders ubiquitous, and therefore augments, the default whiteness of the heteropatriarchal national body imagined by liberal narratives of inclusion. I compare #WelcomeToCanada to Sikh Canadian comedian Jus Reign’s Snapchat story about the Quebec City mosque attack and suggest that his overly faced selfies reveal the violence of a colourblind state gaze that functions like so-called neutral algorithmic vision. Jus Reign’s excessive closeness to his smartphone performs an ambivalent rupture of the universalizing vision on which neoliberal multiculturalism is based, emphasizing the racist logics of facial detection technology even as he characterizes Islamophobia as a particularly US discourse.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".