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Record W2996508898

Accommodating asylum: Improving the housing support system for refugee claimants in Canada

2019· article· en· W2996508898 on OpenAlexaboutno aff
Sruthi Tadepalli

Bibliographic record

VenueSummit (Simon Fraser University) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeAsylum seekerPolitical scienceBusinessLaw
DOInot available

Abstract

fetched live from OpenAlex

Canada has recently seen a dramatic increase in the number of refugee claims being filed in the country. A backlog in the processing of claims has left an increasing number of people dependent on limited support infrastructure. This has been particularly problematic when it comes to housing. Studies have consistently found that refugee claimants face more barriers to accessing housing than other newcomers. This is further complicated by the growing dearth of affordable housing in Canada. The majority of research on this issue has been done at a regional level, with less consideration of federal factors. Using case studies and semi-structured interviews, this study attempts to fill that gap by examining what changes need to be made at a federal level in order to facilitate access to housing support for refugee claimants nationally. The three recommended policy options are designed to improve refugee claimants’ access to housing, and to lower current barriers by facilitating communication and planning.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.475

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0190.003
Scholarly communication0.0040.001
Open science0.0040.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.012
GPT teacher head0.224
Teacher spread0.212 · 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 designQualitative
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
Published2019
Admission routes1
Has abstractyes

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