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Record W4283703295 · doi:10.1177/00113921221102983

Cosmopolitan social infrastructure and immigrant cross-ethnic friendship

2022· article· en· W4283703295 on OpenAlex
Sean Lauer

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCurrent Sociology · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFriendshipEthnic groupImmigrationSociologyCultural diversityDiversity (politics)CosmopolitanismSocial psychologyPolitical sciencePsychologyPoliticsSocial scienceAnthropology

Abstract

fetched live from OpenAlex

How do newcomers make cross-ethnic connections and friendships? This article investigates the role of associations as a location for making cross-ethnic friendships. Cosmopolitan social infrastructure includes public spaces, commercial establishments, and community organizations that attract a diversity of people into interaction. I look specifically at the importance of participation in cosmopolitan associations for cross-ethnic friendship. I approach these questions with an analysis of a nationally representative sample of Canadians collected as part of the Ethnic Diversity Survey. I find that participation in cosmopolitan associations is associated with having cross-ethnic friendship groups. To address the robustness of these findings, I use techniques from both longitudinal and treatment effects analysis. The findings suggest that cosmopolitan social infrastructure contributes to participants’ having cross-ethnic friendship groups.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.500
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.395
Teacher spread0.355 · 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