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Record W2989307395 · doi:10.1177/1354066119883688

Transforming refugees into migrants: institutional change and the politics of international protection

2019· article· en· W2989307395 on OpenAlexfundno aff
Lama Mourad, Kelsey P. Norman

Bibliographic record

VenueEuropean Journal of International Relations · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
FundersHarvard Kennedy SchoolInternational Development Research CentreCarnegie Corporation of New York
KeywordsRefugeeImmigrationPolitical scienceConventionInclusion–exclusion principlePoliticsRefugee lawLimitingPolitical economyInclusion (mineral)Development economicsSociologyPublic administrationEconomic growthLawGender studiesEconomics

Abstract

fetched live from OpenAlex

Since the 2015 refugee “crisis,” much has been made of the distinction between the legal category of refugee and migrant. While migration scholars have accounted for the increased blurring of these two categories through explanations of institutional drift and policy layering, we argue that the intentional policies utilized by states and international organizations to minimize legal avenues for refugees to seek protection should also be considered. We identify four practices of policy “conversion” that have also led to the increasingly problematic distinction between migrants and refugees: (1) limiting access to territory through burden-shifting and other practices of extraterritorialization; (2) limiting access to asylum and local integration through procedural and administrative hindrances; (3) the use of group-based criteria as a basis of exclusion; (4) the inclusion of non-Convention criteria within resettlement schemes. Drawing upon a historical institutionalist approach and a wide array of empirical sources—including 3 years of combined primary field research conducted in Egypt, Lebanon, Morocco, Tunisia, and Turkey between 2013 and 2016—we demonstrate that states are actively pursuing a greater degree of control over the selection of refugees, in practice making refugee resettlement closer to another immigration track rather than a unique status that compels state responsibility.

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)0.012
metaresearch head score (Gemma)0.011
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0120.048
Scholarly communication0.0170.007
Open science0.0010.012
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.024
GPT teacher head0.283
Teacher spread0.259 · 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

Citations63
Published2019
Admission routes1
Has abstractyes

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Same venueEuropean Journal of International RelationsSame topicMigration, Refugees, and IntegrationFrench-language works237,207