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Record W4399488089 · doi:10.22318/icls2024.511783

Newcomer Youths’ Ethical Stances in Representing War And Forced Migration

2024· article· en· W4399488089 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueProceedings. · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsForced migrationComputer sciencePolitical scienceLawRefugee

Abstract

fetched live from OpenAlex

We illustrate how a group of newcomer (refugee) young women of color engaged in filmmaking using stop-motion animation to represent a story of a family becoming refugees in the face of war.We ask the following research question: How did the youth adopt, negotiate, and represent their ethical stances in telling stories of forced migration using stop-motion animation?Our analysis shows that through designing their narratives, and figural and gestural representations of marginal lives, bodies, and interactions, the youth centered axiological dimensions of representing violence, and amplified the ethical complexities experienced by families facing war and violent displacement.The youths' work offers a necessary counter-imaginary for public education in which representational work through creating animations can become a context for making visible and centering ethical and affective dimensions of their experiences of forced migration that are otherwise silenced and invisibilized by the procedurality of refugee resettlement, and in their schools in Canada.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.692
Threshold uncertainty score0.637

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 studies0.0000.000
Scholarly communication0.0000.001
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 head0.025
GPT teacher head0.339
Teacher spread0.314 · 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