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Record W4414024121 · doi:10.1002/ajcp.70018

From greens to safety: Exploring the relationship between outdoor neighborhood conditions, neighborly bonds, and social integration among public housing residents

2025· article· en· W4414024121 on OpenAlexaff
Gum‐Ryeong Park

Bibliographic record

VenueAmerican Journal of Community Psychology · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPlace Attachment and Urban Studies
Canadian institutionsHamilton Health SciencesPublic Health OntarioUniversity of TorontoMcMaster University
Fundersnot available
KeywordsApartmentRentingPublic housingEnvironmental healthEnvironmental qualityRental housingQuality (philosophy)Public healthHealth psychologyBusinessBuilt environmentPsychologySocioeconomicsGeographyGerontologyEconomic growthSociologyPolitical scienceEngineeringMedicineEconomicsCivil engineering

Abstract

fetched live from OpenAlex

This study aims to examine the relationship between outdoor environmental quality, trust in neighbors, and social integration among residents of public rental housing in Seoul, South Korea. It also investigates how neighborly relationships moderate this association. The study uses data from the 2016-2021 Seoul Public Rental Housing Panel Survey (SPRHPS) and applies individual fixed effects models to examine how outdoor environmental quality affects trust in neighbors. It also explores the moderating role of dwelling type characterized by apartment and non-apartment (e.g., single detached house and multiunit housing). Poor outdoor environmental quality, characterized by low greenery, inadequate amenities, and unsafe conditions, was linked to diminished trust in neighbors. Interestingly, the negative impact of these outdoor conditions on neighborly trust was less pronounced among residents of apartments compared to those living in non-apartment settings. This trend was also observed in other outcomes, such as attitudes toward social integration. These findings highlight the importance of both physical environmental improvements and fostering social connections in public housing communities to enhance social trust and overall well-being.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.141
GPT teacher head0.417
Teacher spread0.276 · 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 teacher head, not a consensus.

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
Published2025
Admission routes1
Has abstractyes

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