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Record W4385327177 · doi:10.1093/jrs/fead043

Psychological research evidence in refugee status determination

2023· article· en· W4385327177 on OpenAlexaff
Jane Herlihy, Hilary Evans Cameron, Stuart Turner

Bibliographic record

VenueJournal of Refugee Studies · 2023
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsRefugeePsychologyCollationContext (archaeology)Empirical evidenceScientific evidenceCognitionPresentation (obstetrics)Social psychologyApplied psychologyPolitical scienceComputer scienceGeographyEpistemologyMedicineLaw

Abstract

fetched live from OpenAlex

Abstract This paper presents evidence that refugee status decision makers make assumptions about how humans think and act that are contrary to decades of scientific evidence about human behaviour and cognition (e.g. memory, risk assessment) – including studies and reviews of studies specifically focused on the RSD context. This evidence is not made available to decision makers. In contrast, decision makers regularly benefit from systems and procedures providing relevant, up to date, methodologically sound, impartial, independent, balanced expert evidence pertaining to country of origin information (COI). This paper proposes similar processes for the collation, assessment, and presentation of psychological evidence in order to ensure fairer, more sustainable refugee status decisions.

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)0.031
metaresearch head score (Gemma)0.131
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.031
Threshold uncertainty score0.166

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.131
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0090.006
Science and technology studies0.0010.011
Scholarly communication0.0060.004
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0150.001

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 head0.371
GPT teacher head0.579
Teacher spread0.208 · 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 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

Citations6
Published2023
Admission routes1
Has abstractyes

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