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Record W4417399538 · doi:10.1016/j.cities.2025.106726

Latin American immigrants in urban nature: Exploring mental health and belonging through walking interviews

2025· article· en· W4417399538 on OpenAlexafffundabout
Johanna L. Bock, Lorien Nesbitt, Suzanne Mavoa, Michael J. Meitner

Bibliographic record

VenueCities · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of CanadaState Government of VictoriaDepartment of Jobs, Precincts and RegionsMurdoch Children's Research InstituteVeski
KeywordsLatin AmericansImmigrationMental healthQualitative researchEthnic group

Abstract

fetched live from OpenAlex

Urbanization is linked to mental health challenges, while urban nature is increasingly recognized for its restorative benefits. Yet, access to these benefits remains unequal. Latin American (LA) immigrants—a small but growing population in Canadian cities—may face distinct barriers to engaging with natural spaces, despite often relying on public resources for mental health and belonging. This study explores how urban nature contributes to well-being among LA immigrants in Vancouver, Canada. We conducted 30 semi-structured walking interviews in summer 2024 with participants who had lived in the city for one to ten years. Using reflexive thematic analysis, we examined how interactions with urban nature related to mental health and belonging, and the barriers that shaped these experiences. Nature supported mental health through five pathways: intrinsic qualities, meaningful activities, mindful engagement, personal reflection, and contrast with urban life. Belonging was fostered through engagement, cultural adaptation, and new traditions. However, structural and cultural barriers—including unfamiliar weather, limited prior nature experience, and exclusionary norms—restricted access and reduced benefits. Participants emphasized contemplative, reflective experiences over physical activity or socializing. Urban nature emerged as a space of negotiation where participants actively “tamed” unfamiliar environments to build connection and meaning—highlighting the need for inclusive, culturally responsive nature spaces.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.028
GPT teacher head0.285
Teacher spread0.257 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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 routes3
Has abstractyes

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