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Record W4360989368 · doi:10.25071/1920-7336.40941

Equally Public and Private Refugee Resettlement: The Historical Development of Canada’s Joint Assistance Sponsorship Program

2023· article· en· W4360989368 on OpenAlexaffvenueabout
Rachel McNally

Bibliographic record

VenueRefuge Canada s Journal on Refuge · 2023
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsCarleton University
Fundersnot available
KeywordsRefugeeGovernment (linguistics)Settlement (finance)Joint (building)Political sciencePublic relationsVulnerability (computing)Public administrationBusinessEconomic growthEngineeringFinanceLawComputer securityEconomics

Abstract

fetched live from OpenAlex

For over 40 years, Canada’s Joint Assistance Sponsorship Program has combined government financial assistance, professional settlement services, and private sponsor settlement support for refugees identified as having “special needs.” With high public and private involvement, the program offers another potential model for sponsorship, yet existing knowledge about the program is limited. This article explores the historical development of the program, highlighting three time periods: 1979–1981, when it launched; 1998–2001, when it welcomed thousands of Kosovars and expanded as selection criteria prioritized vulnerability; and 2014–2019, as it increasingly competed with other sponsorship programs.

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)0.004
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: none
Teacher disagreement score0.128
Threshold uncertainty score0.932

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0210.009
Scholarly communication0.0060.002
Open science0.0010.004
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0070.000

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 head0.061
GPT teacher head0.315
Teacher spread0.254 · 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

Citations5
Published2023
Admission routes3
Has abstractyes

Explore more

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