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Record W2151293937 · doi:10.1177/1363461506061757

Longitudinal Research to Promote Effective Refugee Resettlement

2006· article· en· W2151293937 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueTranscultural Psychiatry · 2006
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRefugeeGenerosityEthnic groupMental healthPolitical scienceCoping (psychology)Displaced personReputationInternally displaced personPublic relationsEconomic growthPsychologySociologyLawPsychiatry

Abstract

fetched live from OpenAlex

Canada's relative generosity in admitting refugees and fairness in considering refugee claims has earned this country an enviable reputation. However, having opened its doors to those selected, Canada's resettlement policies and programs fail to provide for their needs, and to promote their optimal adaptation. Based on a decade-long investigation of the resettlement of more than 1300 Southeast Asian refugee--'Boat People'--the current report examines how research concerning (a) the impact of pre-migration trauma; (b) the mental health impact of social resources such as the like-ethnic community, refugee sponsorship programs, and language training; and (c) individual coping strategies such as suppressing the past, can contribute both to theory and to improving policy and practice. The presentation acknowledges the contributions of Dr. Alexander H. Leighton by demonstrating the importance of his insistence on the need for a longitudinal perspective both for conducting research and for planning programs and services.

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.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.781
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.043
GPT teacher head0.407
Teacher spread0.364 · 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