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Record W3123745522 · doi:10.1093/jrs/feaa121

Governing Practices and Strategic Narratives for Syrian Refugee Returns

2020· article· en· W3123745522 on OpenAlex
Zeynep Şahin Mencütek

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Refugee Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsRefugeeNarrativeGeopoliticsTurkishPolitical sciencePeacebuildingRepatriationPsychological interventionGovernment (linguistics)Political economySociologyPublic administrationLawPoliticsPsychology

Abstract

fetched live from OpenAlex

Abstract How do host states attempt to speed up returns of refugees before peacebuilding and the lack of official arrangements with the home state? Building on the conceptual framework, which coalesces governing practices, strategic narratives, and issue linkages, the article explains the early stages of policy formulation and discourses on refugee returns. Empirically, it draws from Turkey’s return initiatives targeting Syrians since 2016. It argues that the Turkish government seeks to advance in (1) practices promoting self-organized voluntary returns of a small number of refugees and (2) the preparation of ground for mass repatriation and resettlement back to Northern Syria. The strategic return narrative has 2-fold target audiences and aims. While keeping the domestic constituency stands as the main motivation by conveying the message of ‘Syrians are returning’, legitimizing unilateral cross-border interventions targets the international audience. The article contributes to the lack of research on the governance of refugee returns by examining the host states’ strategic narrating in relation to the domestic and geopolitical interests.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.743
Threshold uncertainty score0.314

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.158
GPT teacher head0.423
Teacher spread0.264 · 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