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Record W4238988923 · doi:10.32920/ryerson.14645205

Welcoming communities and immigrant integration in Newfoundland and Labrador

2021· preprint· en· W4238988923 on OpenAlexaffabout
Natasha M. Clark

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsImmigrationSettlement (finance)Inclusion (mineral)Social integrationCommunity organizationField (mathematics)Political scienceSociologyEconomic growthGeographyGender studiesPublic relationsLawBusiness

Abstract

fetched live from OpenAlex

The term 'welcoming community' has arisen within the field of immigration studies as a concept that seeks to address ways in which communities welcome and integrate immigrants. This paper explores the concept of a welcoming community and its impact on the social integration of immigrants to smaller centres, specifically to the City of St. John's in the Province of Newfoundland and Labrador, using a social inclusion framework. Through an examination of the integration policies and programs undertaken in the Province and how immigrants interact with these services. I find the elements of a welcoming community exist in St. John's and that immigrants' frequency and intensity of contact with institutions that directly support settlement is high in St. John's. However, it is premature to conclude, given the recent implementation of the immigration policy in the Province and low numbers of contacts made with other institutions, that St. John's is a welcoming community and that this translates into successful social integration.

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)0.003
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 score0.049
Threshold uncertainty score0.359

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0140.006
Scholarly communication0.0050.002
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.021
GPT teacher head0.253
Teacher spread0.232 · 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
Published2021
Admission routes2
Has abstractyes

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