MétaCan
Menu
Back to cohort
Record W3044095195 · doi:10.1177/2399654420943593

The borderization of waiting: Negotiating borders and migration in the 2011 Syrian civil conflict

2020· article· en· W3044095195 on OpenAlexaffabout
Suzan Ilcan

Bibliographic record

VenueEnvironment and Planning C Politics and Space · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsNegotiationPrecarityAgency (philosophy)InvisibilityState (computer science)Political scienceIrregular migrationPoliticsPolitical economyArmed conflictBorder SecuritySociologyPublic administrationLawSocial science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0190.020
Scholarly communication0.0060.004
Open science0.0010.007
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.020
GPT teacher head0.265
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations26
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueEnvironment and Planning C Politics and SpaceSame topicMigration, Refugees, and IntegrationFrench-language works237,207