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Record W4243211495 · doi:10.32920/ryerson.14652699

An Investigation of the Relationship Between a Designated Country of Origin List and Access to Legal Aid In Ontario

2021· preprint· en· W4243211495 on OpenAlexaffabout
Alexandra Del Bel Belluz

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsMcMaster UniversityToronto Metropolitan University
Fundersnot available
KeywordsLegislationRefugeeAppealTimelineImmigrationSettlement (finance)Political scienceExploratory researchPublic administrationBusinessLawPublic relationsSociologyGeographyFinance

Abstract

fetched live from OpenAlex

This qualitative and exploratory research project focuses on the Designated Country of Origin policy in the upcoming legislation, Bill C-31: the Protecting Canada’s Immigration System Act and its relationship to Legal Aid Ontario. Through interviews with refugee lawyers and refugee settlement workers as well as analysis of policy and Legal Aid documents, research findings provide insight into the effect the Designated Country of Origin list will potentially have on access to Legal Aid Ontario services for refugee claimants from designated countries. Research recommendations point to the importance of reconsidering the manner in which Legal Aid funding is disbursed, as well as policy implications including adjusting the timelines outlined in the upcoming legislation, implementing more stringent designation policies and access to appeal processes.

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)0.004
metaresearch head score (Gemma)0.012
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 score0.079
Threshold uncertainty score0.576

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0170.010
Scholarly communication0.0040.002
Open science0.0010.005
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 head0.146
GPT teacher head0.389
Teacher spread0.243 · 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

Citations1
Published2021
Admission routes2
Has abstractyes

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