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Record W4386267333 · doi:10.33679/rmi.v1i1.2357

Exploring Mexican Immigrant Settlement in the Suburbs of Vancouver

2022· article· en· W4386267333 on OpenAlexaffabout
Anabel López Salinas, Carlos Teixiera

Bibliographic record

VenueMigraciones internacionales · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsImmigrationSettlement (finance)SuburbanizationDestinationsEthnic groupGeographyDiversity (politics)PoliticsEconomic growthHuman settlementPolitical scienceBusinessTourism

Abstract

fetched live from OpenAlex

In the current age of migration, suburbs in many Canadian cities are becoming important ports of entry for new immigrants from around the world. This has led to a growth in cultural, ethnic, and racial diversity in the suburbs reflecting global migration patterns. In Vancouver, Canada, the growing “suburbanization” of immigrants is shaping social, cultural, economic, and political landscapes in these areas. Through interviews with 60 key informants, we explore the settlement of Mexican immigrants in Burnaby, Surrey, and Abbotsford, fast-growing Canadian communities, and popular destinations for Mexican immigrants. The findings reveal that Mexican immigrants living in the suburbs of Vancouver face numerous barriers, including lack of access to affordable housing to rent or buy, lack of information on settlement services, and difficulty securing acceptable employment.

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)0.001
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.220

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0140.003
Scholarly communication0.0040.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.124
GPT teacher head0.307
Teacher spread0.183 · 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

Citations2
Published2022
Admission routes2
Has abstractyes

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