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Record W4210853299 · doi:10.1177/1086296x221076431

Leading Literate Lives: Afghan Refugee Children in a First-Asylum Country

2022· article· en· W4210853299 on OpenAlexaff
Assadullah Sadiq

Bibliographic record

VenueJournal of Literacy Research · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and experiences of immigrants and refugees
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRefugeeEthnographyLiteracyReading (process)AfghanPedagogyPsychologySociologyGender studiesPolitical science

Abstract

fetched live from OpenAlex

Most refugees in countries of permanent resettlement arrive from first-asylum countries – countries where refugees initially move to escape crisis in their homelands. Their pre-resettlement educational experiences have largely been undocumented. This qualitative ethnographic study describes the literacy practices of four elementary-aged Afghan refugee children in Pakistan. The findings revealed rich and various literacy practices these children and their families engaged in at home and beyond, such as practicing religious supplications or engaging in storytelling, trying to read and write in Urdu and English, reading the Quran or religious supplications, and helping others with their own literacy development. The parents and guardians highly valued literacy and believed it instilled manners, morals, and essential skills in their children. This research includes important implications for teachers working with refugee students.

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)0.002
metaresearch head score (Gemma)0.003
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0210.010
Scholarly communication0.0060.004
Open science0.0010.008
Research integrity0.0020.004
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 head0.036
GPT teacher head0.430
Teacher spread0.394 · 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
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

Citations12
Published2022
Admission routes1
Has abstractyes

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