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Record W4412855486 · doi:10.1177/14687968251364351

Forensic and humanitarian frames: Mediating migration as crisis

2025· article· en· W4412855486 on OpenAlexaff
Krista Lynes

Bibliographic record

VenueEthnicities · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicInterdisciplinary Cultural and Social Studies
Canadian institutionsConcordia University
Fundersnot available
KeywordsCriminologyHumanitarian crisisPolitical scienceBorder SecurityIrregular migrationSociologyPolitical economyLawRefugeeEthnology

Abstract

fetched live from OpenAlex

This paper examines the visual culture of mediating migration as a “crisis,” arguing that responses to the movement of peoples (especially into the Global North) is animated by two frames: the forensic and the humanitarian. While these appear to be contradictory image regimes—one relying on data, maps and metrics, the other on iconic portraits of human suffering—the paper argues that it is the vacillation between these two poles that creates the dynamic force of the surge of images of “migrant crises.” Using the image of the thaumatrope – a visual tool for tricking the eye into seeing two images at once – this paper explores how processes of mediation train viewers to see images as data and data as images, and thus to be caught within an ideological framework of crisis. It seeks also to provide examples for intervening in the vacillation between humanitarianism and forensics through activist appropriations of migration data.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.214
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
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 head0.022
GPT teacher head0.350
Teacher spread0.328 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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