“We must use every legal means to … put them behind bars, or to run them out of town”: Assembling citizenship deservingness in Toronto
Bibliographic record
Abstract
This paper examines the assemblage and reassemblage of citizenship deservingness in Canada in the past few decades. By citizenship deservingness, I refer to the ways immigrant and racialized persons are accorded value and opportunity to access and retain formal citizenship status, including the right to remain in Canada. In order to make this argument, I examine the response to a 2012 shooting in Scarborough, an “inner suburb” of Toronto, Canada. I situate the shooting responses alongside policy and discursive changes that have made it easier to deport permanent residents from Canada if they have committed certain criminal acts. As scholars have noted, the targets of such policies are often the same individuals profiled and typecast as committing criminal acts—namely, immigrant and racialized men. In the Scarborough shooting, Jamaican men were specifically criminalized and targeted for exile from the city and country. My analysis demonstrates how, through this process, discourses of race and space came together to produce and legitimate policy changes that continue to erode the rights accorded to permanent residents and citizens.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.060 | 0.030 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".