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Record W4414759698 · doi:10.31235/osf.io/56drf_v1

How does Coethnicity with Refugees Shape their Reception? Evidence from Afghan Refugees in Pakistan

2025· article· en· W4414759698 on OpenAlexfundno aff
Mashail Malik, Niloufer Siddiqui, Yang‐Yang Zhou

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in MENA
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaCanadian Institute for Advanced ResearchUnited States Institute of Peace
KeywordsRefugeeEthnic groupSalientIdentity (music)Face (sociological concept)ImmigrationEthnographyCountry of origin

Abstract

fetched live from OpenAlex

How does coethnicity shape host attitudes toward refugees? Existing research finds that cultural threat drives anti-refugee attitudes, so refugees who share an ethnic background with host populations should face less backlash. We examine this in Pakistan, where both refugee and host communities include substantial Pashtun populations. Drawing on survey experimental, observational, and qualitative data, we find that while a conjoint experiment shows a comparative preference for coethnics, this result masks both low absolute support and sharp internal variation. Coethnic hosts in regions where they are ethnic minorities express more inclusive attitudes than those living in their ethnic homeland. We argue that the impact of coethnicity can depend on local demography: where coethnic hosts are a marginalized minority, coethnicity with refugees can carry both instrumental and symbolic value. These findings complicate standard assumptions about the primacy of cultural threat and highlight the need to understand subnational variation in refugee-host dynamics.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.372
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.349
Teacher spread0.326 · 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 designObservational
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 routes1
Has abstractyes

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