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Record W1891062734 · doi:10.25071/1920-7336.26039

The Use of COI in the Refugee Status Determination Process in the UK: Looking Back, Reaching Forward

2008· article· en· W1891062734 on OpenAlexvenueno aff
Jo Pettitt, Laurel Townhead, Stéphanie Huber

Bibliographic record

VenueRefuge Canada s Journal on Refuge · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeImmigrationAppealContext (archaeology)Decision-makingProcess (computing)Political sciencePublic relationsGeographyLawBusinessComputer scienceMarketingArchaeology

Abstract

fetched live from OpenAlex

In the context of Refugee Status Determination (RSD), while the primary form of evidence is the testimony of the asylum applicant, objective evidence in the form of Country of Origin Information (COI) is recognized as an important— and potentially crucial—tool in decision making. A research project of the Research and Information Unit (RIU) of the Immigration Advisory Service (IAS) examines the use of COI in the RSD process in the UK from initial decision to fi nal appeal. Th e fi ndings highlight the high level of inconsistency in the understanding of and the application of COI in RSD in the UK. It will demonstrate the need for this issue to be urgently addressed in the interest of just and effective decision making in the UK, and help inform discussions at the European and international levels.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.968
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.042
GPT teacher head0.305
Teacher spread0.264 · 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 designNot applicable
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

Citations6
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueRefuge Canada s Journal on RefugeSame topicMigration, Refugees, and IntegrationFrench-language works237,207