Theorizing claims making across the citizenship spectrum: three case studies
Bibliographic record
Abstract
Within the scholarly literature, practices of claims-making by citizens and non-citizens are seldom juxtaposed, and there is limited attention to claims-making by or on behalf of stateless people. This article counters these tendencies by inductively theorizing different types of citizenship claims made by or on behalf of non-citizens, citizens and stateless people in three separate Canadian case studies. These cases are: COVID-19 era regulation of precarious migrants; citizen opposition to public health mandates and vaccines in 2022; and the pro-Palestine encampment at the University of Toronto in 2024. While drawn from Canada, the case studies have similar counterparts in other countries, and they also illuminate the relevance of theorizing claims-making in relation to the deservingness of non-citizens, the entitlement of citizens, and solidarity with stateless Palestinians. We therefore argue that status across the citizenship spectrum exerts effects on where claims are directed, and how they are articulated, performed and heard by state actors and others.
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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 | 0.022 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.035 | 0.047 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".