Non-Belonging: borders, boundaries, and bodies at the interface of migration and citizenship studies
Bibliographic record
Abstract
Non-belonging is an undertheorized current in work on migration and citizenship, too often understood as simply the absence of belonging. We define non-belonging as an actively constructed space and logic that entails the denial of personhood, where personhood captures one’s sense of self, one’s capacity to act, as well as the human and citizenship rights tied to this. We suggest that distinct processes interact to foster spaces and logics of non-belonging: (1) bordering through state practices; and (2) boundary formations through representation, with (3) both of these inscribed on bodies. We illustrate our framework through the example of a legal case regarding the repatriation of Dutch women who joined the Islamic State. We also apply our framework to examples from our previous research on Muslim masculinities in Canada and Germany and Turkish mothers in Berlin who circumvent immigrant stigma by sending their children to international schools to show the framework’s utility in analyzing non-belonging writ large.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.074 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| 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".