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Record W3125267640 · doi:10.3390/journalmedia2010003

Digital Media Production of Refugee-Background Youth: A Scoping Review

2021· review· en· W3125267640 on OpenAlexaff
Amir Michalovich

Bibliographic record

VenueJournalism and Media · 2021
Typereview
Languageen
FieldSocial Sciences
TopicEducation and experiences of immigrants and refugees
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRefugeeSocial mediaDigital mediaMedia literacyContext (archaeology)Digital literacySociologyLiteracyBest practicePublic relationsPolitical sciencePedagogyGeography

Abstract

fetched live from OpenAlex

Reviews of research have provided insights into the digital media production practices of youth in and out of school. Although such practices hold promise for the language and literacy education of refugee-background youth, no review has yet integrated findings across studies and different digital media production practices to explore this promise. This scoping review summarizes and discusses the key findings from research on varied types of digital media produced specifically by refugee-background youth in and out of school. It situates digital media production practices in the context of this diverse population, which experiences forced migration, and highlights 5 main themes from findings in 42 reviewed articles. Digital media production afforded refugee-background youth: (1) Ownership of representations across time and space; (2) opportunity to expand, strengthen, or maintain social networks; (3) identity work; (4) visibility and engagement with audiences; and (5) communication and embodied learning through multimodal literacies.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0110.010
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.108
GPT teacher head0.425
Teacher spread0.317 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreReview

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

Citations20
Published2021
Admission routes1
Has abstractyes

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