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Record W3215824258 · doi:10.3389/fhumd.2021.668264

Inclusive Resettlement? Integration Pathways of Resettled Refugees With Disabilities in Germany and Canada

2021· article· en· W3215824258 on OpenAlexaffabout
Annette Korntheuer, Michaela Hynie, Martha Kleist, Safwathullah Farooqui, Eva Lutter, Manuela Westphal

Bibliographic record

VenueFrontiers in Human Dynamics · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsYork University
Fundersnot available
KeywordsRefugeeAgency (philosophy)Context (archaeology)ImmigrationIntersectionalityPolitical scienceSettlement (finance)Gender studiesNarrativeDisability studiesSociologySocial scienceGeography

Abstract

fetched live from OpenAlex

The purpose of this article is to explore the existing intersectional knowledge on integration and resettlement of refugees with disabilities in two of the top five resettlement countries in the world, Germany and Canada. There is limited research on the intersection of migration and disability, especially in the context of refugee resettlement. Reflecting the dominant pathways of migration in each country, what little research there is focuses on asylum seekers in Germany, and immigrants in Canada. The review describes settlement programs in each country. We draw from the global literature around forced migration and disability, as well as disability and migration more broadly in each country, to enhance the limited existing research and conduct an intersectional analysis at the level of systems, discourses and subjective narratives. Findings highlight three dominant themes that weave across all three levels: being a “burden” on society, being invisible, and agency and resistance. Finally, drawing from the theoretical stance of Disability Studies, critical, and holistic integration theories we discuss how this intersectional analysis highlights the importance of reshaping the policies, discourse and definition of integration, and the consequences this can have on research, service delivery, and evaluation of integration and resettlement.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.542
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.010
GPT teacher head0.284
Teacher spread0.274 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations20
Published2021
Admission routes2
Has abstractyes

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