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Record W2761354944 · doi:10.21810/strm.v9i2.229

Re-Orienting Refugee Representation? A Multimodal Analysis of Syrian Refugee Representation on the Social Media Platform "Humans of New York"

2017· article· en· W2761354944 on OpenAlex

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueStream Interdisciplinary Journal of Communication · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicMiddle East Politics and Society
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsOrientalismRefugeeNarrativeMainstreamRepresentation (politics)SemioticsSocial semioticsIslamSociologySyrian refugeesSocial mediaMedia studiesAestheticsGender studiesEpistemologyLiteraturePolitical scienceHistoryPoliticsArtPhilosophyLaw

Abstract

fetched live from OpenAlex

This paper examines a selection of photo-narratives from the social media account Humans of New York, which documented the experiences of Syrian refugees in the fall of 2015. It questions how an alternative media platform may challenge or reinforce traditional tropes utilized by mainstream media to represent a marginalized group such as Syrian refugees. To engage in the analysis, codes were developed from the literature review on Orientalism, neo-Orientalism, media representations of Islam and of refugees, as well as from theories of visual social semiotics and narrative analysis. The results suggest that while alternative platforms may challenge aspects of the Orientalist discourse, this discourse is also seen to adapt and persist through more subtle manifestations. The HONY audience is more likely to affirm representations that fit within the neo-liberal notion of who is an acceptable and “worthy” refugee.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.319
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.101
GPT teacher head0.421
Teacher spread0.320 · 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