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Record W4411328986 · doi:10.1080/08865655.2025.2516225

Borderland Narratives of Hostility and Solidarity: Perceptions of Migrants in Social Media Discourse in Bosnia and Herzegovina

2025· article· en· W4411328986 on OpenAlexvenueno aff
Nataša Vučenović

Bibliographic record

VenueJournal of Borderlands Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsSolidarityHostilityNarrativePerceptionSociologyPolitical scienceGender studiesSocial psychologyPsychologyLinguisticsLawPhilosophyPolitics

Abstract

fetched live from OpenAlex

Bosnia and Herzegovina’s internal dynamics and historically contested identities have long reinforced symbolic borders among its three major ethnic groups. Due to persistent political tensions and economic instability, the country has traditionally been characterized by high emigration rates. However, in recent years, it has functioned as both a transit and even a target country for migrants, becoming a borderland for bodies in movement too. This study analyzes the portrayal of migrants in social media discourse in BiH with the aim of examining the construction of narratives of hostility and solidarity. It employs a mixed-methods approach, integrating Qualitative Content Analysis (QCA) and Critical Discourse Analysis (CDA). The findings suggest that perceptions of hostility and solidarity are influenced by gender and ethnicity/religion of the commenter. Furthermore, the study highlights how anti-immigrant discourse operates within a broader ideological framework shaped by cultural threats and border anxieties.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score0.873

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.023
GPT teacher head0.375
Teacher spread0.352 · 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 designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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