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Record W7061456015

Post-2014 migrants' access to housing, employment and other crucial resources in small- and medium-sized towns and rural areas in Canada: Country Reports on integration

2022· report· en· W7061456015 on OpenAlexaboutno aff

Bibliographic record

VenueYork University Digital Library (York University) · 2022
Typereport
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersEuropean Commission
KeywordsSettlement (finance)Rural areaImmigrationUnemploymentCredentialService (business)Service providerRefugeeDisplaced person
DOInot available

Abstract

fetched live from OpenAlex

This report looks at migrants’ access to housing, employment, and other relevant resources in six different small and medium-sized towns and rural areas in Canada between 2016 and 2021. Primarily based on interviews conducted in each of the six selected municipalities, secondary data analysis and a policy literature review, it provides an overview of the concrete barriers that migrants face in relation to housing and employment; the local actors who are involved in, and/or seen as responsible for, facilitating their access; any concrete local measures or practices that help or hinder this access; and the specific target groups of these measures, initiatives or practices. The report finds that the concrete barriers facing migrant access to housing are affordability, availability, and size. These factors were particularly acute in Ontario and B.C. where a housing crisis has driven up the average cost of a home and decreased availability. During the study period, Canada possessed low unemployment rates, however, one of the concrete barriers regarding economic integration was foreign credential recognition and language acquisition (English or French). The local actors who were involved included immigrant settlement service organizations, provincial employment ministries, faith organizations or groups of individuals (involved in private sponsorship), provincial/regional chambers of commerce and community service organizations. The measures and practices included employment matching and preparation services, language training programs, job banks, mentoring programs, paid internships, targeted migrant hiring initiatives by municipal and community-service organizations, skills upgrading programs and municipal integration policies. The specific target groups of these measures included immigrants (both economic and resettled refugees) as well as residents.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.039
Threshold uncertainty score0.282

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0050.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0000.001
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 head0.013
GPT teacher head0.198
Teacher spread0.185 · 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
Published2022
Admission routes1
Has abstractyes

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