Governance through discipline in the neighbourhood: Syrian refugees and Turkish citizens in urban life
Bibliographic record
Abstract
In this paper, we contend that the regulation of refugees by means of discipline is not limited to camps; it also takes place within the context of urban life. This is particularly relevant for Turkey, where only 1.5% of the 3.7 million Syrian refugees live in the camps while the rest are dispersed across Turkish cities. Our fieldwork conducted in the city of İzmir indicates that the processes of governing refugees extend into the neighbourhoods through “informal” disciplinary techniques deployed by citizens. The disciplinary techniques could take various forms, such as socio‐spatial distancing and corporal violence. The discipline in the neighbourhoods sets limits on the Syrians’ collective presence in the city and inculcates the possible results they could face if they attempt to breach these limits. The disciplinary actions of the host community unfold in the context of the Turkish state's legal regulations and discursive strategies that circumscribe Syrians to a specific political position relative to the state and, by extension, to the citizens. The process of disciplining refugees in the neighbourhoods depoliticizes Syrian refugees by obstructing their collective will to contest their precarious status and the exploitative working conditions.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.023 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| 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".