The borderization of waiting: Negotiating borders and migration in the 2011 Syrian civil conflict
Bibliographic record
Abstract
The past several decades have witnessed diverse techniques of border control and migrant experiences and negotiations of border controls. This article focusses on the spatio-temporal dimensions of border control that underscore the deceleration of migration movements and stimulate certain kinds of agency, processes that bring attention to what is referred to as the borderization of waiting. Drawing on and contributing to critical migration and border studies, the analysis first draws attention to city street protests in Syria that demanded political change, which in turn created powerful responses including the expansion of protests against the state, the circulation of fear by the state, and the movements of people out of Syria. It then demonstrates how the borderization of waiting during the 2011 Syrian civil conflict occurs at many different points along migrant journeys and encompasses not only precarity but also fear, insecurity, invisibility, and presence. This form of waiting encourages ‘agency-in-displacement,’ which involves strategizing journeys and negotiating inter-state military checkpoints, state territorial borders, and holding zones in order for people on the move to access safety and protection. The analysis draws on policy, program, and scholarly documents, and on a selection of fifty-five in-depth, interviews with Syrians, now resettled in Canada, about their experiences and negotiations of border controls during their departures from the civil conflict.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.020 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".