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Record W4399489377 · doi:10.3390/youth4020057

Making Homes in Un-Homelike Places among Young People in Vancouver: Implications for Homelessness Prevention

2024· article· en· W4399489377 on OpenAlexaffabout
Daniel Manson, Danya Fast

Bibliographic record

VenueYouth · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsBritish Columbia Centre on Substance UseUniversity of British Columbia
Fundersnot available
KeywordsEthnographyFeelingSocialitySociologyCriminologyGender studiesPsychologySocial psychology

Abstract

fetched live from OpenAlex

This article explores the experiences of young people navigating an evolving system of housing and homelessness services in Vancouver, Canada. Despite recent shifts toward Housing First policies and calls for prevention-oriented initiatives, many young people continue to rely on temporary emergency accommodations. Amid a surge in youth homelessness and unstable housing in Vancouver, our study examines young people’s “homing” strategies across time and place and temporary and more permanent living environments. We draw from an ongoing ethnographic study that began in 2021 and has involved over 70 interviews and 100 h of fieldwork with 54 young people aged 19 to 29. Our findings emphasize that feeling at home extends beyond having a roof over one’s head for an extended period of time. A focus on homing strategies—that is, the day-to-day practices, routines, and forms of sociality that generate a sense of stability and care even in un-homelike places—highlights how young people can be better supported in making themselves at home in the places where they live, potentially preventing returns to street-based homelessness. This study contributes insights to youth homelessness prevention policies, urging a strengths-based approach that aligns with young people’s needs, priorities, and desires for homemaking.

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)0.001
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 score0.522
Threshold uncertainty score0.686

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.062
GPT teacher head0.415
Teacher spread0.353 · 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

Citations4
Published2024
Admission routes2
Has abstractyes

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