MétaCan
Menu
Back to cohort
Record W4389385543 · doi:10.1080/08865655.2023.2289105

Gazing Toward and Beyond the Borders: Syrian Refugees and Organizations Supporting Them in Turkey

2023· article· en· W4389385543 on OpenAlexvenueno aff
Izabela Kujawa, Izabella Main

Bibliographic record

VenueJournal of Borderlands Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
FundersHorizon 2020European Commission
KeywordsSyrian refugeesRefugeePolitical scienceLaw

Abstract

fetched live from OpenAlex

We investigate the meanings of borders for Syrians based in Turkey and for the efforts of the civil society organizations supporting them.We look at how being placed within specific borderscapes determines Syrians' everyday lives and CSOs' activities in Istanbul and Gaziantep.The scholarly literature usually explores experiences of borders and the consequences of bordering practices for migrants, refugees, and asylum seekers while focusing solely on those of the country in which the foreigners currently reside.We point out that while people's experiences and CSOs' actions greatly depend on regulations, policies, and the implementation thereof, in this case, of the Turkish refugee regime, they also depend on people's gaze at and beyond the borders toward Syria and Western countries; they are also affected by what was, is, or could be happening on their other sides.Rather than viewing borders as static lines, we approach them as an element of borderscapes and explore how they influence people's general situation as well as their day-to-day social relations affecting their identities and group formation.We demonstrate that these borderscapes shape the processes of becoming and belonging even long after the physical border has been crossed and continually impress the work of the CSOs that provide the support in this field.

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 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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.116
Threshold uncertainty score0.484

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.032
GPT teacher head0.357
Teacher spread0.325 · 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 teacher head, 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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Borderlands StudiesSame topicMigration, Refugees, and IntegrationFrench-language works237,207