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Record W4414592010 · doi:10.1080/10646175.2025.2558806

Bordering Vulnerability: Media Portrayal of Climate Migrants in Quebec’s Visual Narrative

2025· article· en· W4414592010 on OpenAlexaffabout
Sarah Lajeunesse, Jessica Auchter, Yannick Dufresne

Bibliographic record

VenueHoward Journal of Communications · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsNarrativeVisual mediaImmigrationVisual rhetoricRace (biology)Visual cultureEthnic groupPrecarity

Abstract

fetched live from OpenAlex

How are migrants and refugees represented in media visual discourse in Quebec? This article explores the representation of migrants and refugees, particularly climate migrants, in Quebec media visual representations. Climate migrants, often perceived as “simple” migrants or as refugees due to a hitherto incomplete international legal definition, are faced with increasingly frequent, urgent, and irreversible displacements. Their vulnerability is exacerbated by the intensification of border restrictions, repulsion based on national security, and political and media discourses. In this context, we specifically focus on the precarious situation of climate migrants at the land border between Canada and the United States, particularly at “regular” and “irregular” entry points in Quebec. In exploratory research, this paper examines the media visual portrayal of these individuals and of topics related to them. We focus on a visual analysis of key Quebec written media between 2018 and 2023. It aims to identify the types of content presented and the key actors involved, analyze the images compositions, elements, and symbols to understand the messages they convey and interpret these messages in the context of the target audience and the media environment. Additionally, it discusses the use of visual rhetoric and its impact on the perception of migration issues. This study contributes to a better understanding of how migrants are portrayed, and the implications of such portrayals for public perception and attitudes toward migration.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.533
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.103
GPT teacher head0.405
Teacher spread0.301 · 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
Published2025
Admission routes2
Has abstractyes

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