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Record W4243621228 · doi:10.32920/ryerson.14661258.v1

What to expect? : examining the role of pre-departure cultural orientations

2021· preprint· en· W4243621228 on OpenAlexaffabout
Ashley Korn

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsToronto Metropolitan University
FundersUnited Nations High Commissioner for Refugees
KeywordsRefugeeExploratory researchPolitical scienceImmigrationSettlement (finance)OfficerSocial capitalPublic relationsPsychologySociologyBusinessSocial science

Abstract

fetched live from OpenAlex

Providing relevant pre-migration information for newcomers to Canada can have many potential benefits, however there is a gap in understanding the implications of pre-departure cultural orientations (P-DCO) on refugee settlement. This research focuses on the unique resettlement experiences of privately sponsored refugees entering Canada through the Student Refugee Program (SRP). The purpose of this research is to understand how P-DCO impacts the resettlement of SRP participants and identify the effectiveness of such programs. The study uses the theoretical lens of cultural and social capital to understand the role of P-DCO in the migration and resettlement of SRP participants. Individual interviews were conducted with 6 SRP participants, as well as a key informant interview with the SRP Senior Program Officer. This exploratory study contributes to an enhanced understanding of the effectiveness of P-DCO for refugees in their resettlement and advocates further research for other immigrant categories.

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)0.010
metaresearch head score (Gemma)0.023
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.221
Threshold uncertainty score0.439

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0050.008
Scholarly communication0.0080.004
Open science0.0020.005
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.044
GPT teacher head0.376
Teacher spread0.332 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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