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Record W7029167885

Integration of government assisted refugees in British Columbia

2006· dissertation· en· W7029167885 on OpenAlexaboutno aff

Bibliographic record

VenueSummit (Simon Fraser University) · 2006
Typedissertation
Languageen
FieldArts and Humanities
TopicMedical History and Research
Canadian institutionsnot available
FundersUnited Nations High Commissioner for Refugees
KeywordsRefugeeReceiptImmigrationGovernment (linguistics)Status quoWelfare
DOInot available

Abstract

fetched live from OpenAlex

Why are some refugees more likely to receive provincial income assistance than others? This study looks at 3,608 Government Assisted Refugees destined to British Columbia from 1998 to 2004. By combining federal immigration data with provincial data on welfare, it finds that one in four refugees received welfare. Using logistical regression, the explanatory strength of the model is low. However, the following categories are :jhown to be significant predictors of receipt of income assistance: refugees with a formal trade, dependants, and women were more likely to be welfare recipients whereas refugees with knowledge of English, refugees from Africahiiddle East and AsiaPacific, rehgees destined to Surrey, and a common law marital status were less likely. Women at risk and urgent protection cases were hypothesized to be significant but were not. With these findings, this study supports the status quo but recommends language training overseas for refugees if additional funds are available.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.927
Threshold uncertainty score0.997

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.220
Teacher spread0.204 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

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