MétaCan
Menu
Back to cohort
Record W4392927032 · doi:10.1080/07352166.2024.2326487

The neighbor spectrum in community housing: Pro-social, anti-social and asocial neighboring in Vancouver

2024· article· en· W4392927032 on OpenAlexaffabout
Meg Holden, Robyn Lee, Flandrine Lusson, Lainey Martin, Dorin Vaez Mahdavi, Sara Emami, Yushu Zhu

Bibliographic record

VenueJournal of Urban Affairs · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsSimon Fraser University
FundersAmerican College of Foot and Ankle Surgeons
KeywordsContext (archaeology)Vulnerability (computing)Inclusion (mineral)Diversity (politics)SociologyPublic housingEconomic growthPolitical scienceGeographyGender studies

Abstract

fetched live from OpenAlex

This article presents focus group research with community housing residents in Vancouver, Canada, investigating the role, activities, and importance of neighboring to these individuals living in vulnerable situations. Neighborly relationships play a key role in connecting the private home with the larger urban community through processes of home-making, social inclusion and integration, but an increasing share of urbanites are excluded from the structural and social expectations of good neighboring. Although neighbors constitute weaker and different ties than friends and family, and although contemporary urban community housing situations present barriers to good neighboring, neighboring is nonetheless essential to urban quality of life. We propose a conceptual frame of a spectrum of neighboring and find that pro-social neighboring, anti-social neighboring, and a middle zone of asocial neighboring, all are important aspects of life in community housing that are also defined in a context-specific way by community housing residents. The outcomes of this research highlight the need for urban social and housing policy that addresses neighboring across the spectrum as an important part of social inclusion and well-being efforts in cities contending with increasing density, diversity, and vulnerability.

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 score0.259
Threshold uncertainty score0.521

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.003
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0000.001
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 head0.024
GPT teacher head0.295
Teacher spread0.271 · 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

Citations3
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Urban AffairsSame topicMigration, Aging, and Tourism StudiesFrench-language works237,207