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Record W3095540494 · doi:10.1111/cag.12658

Canadian homeless mobilities: Tracing the inter‐regional movements of At Home/Chez Soi participants

2020· article· en· W3095540494 on OpenAlexafffundvenueabout
Drew F. Kaufman

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2020
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsMobilitiesInterpersonal communicationPersonal mobilitySociologyDemographic economicsSocial scienceEconomics

Abstract

fetched live from OpenAlex

People experiencing homelessness are simultaneously socially and physically mobile. Individuals move through periods of housing stability and houselessness and varying degrees of financial (in)stability, and between different geographic spaces. Research concerning homeless mobilities emphasizes moves within cities and reveals seven factors deserving attention: housing; labour markets; social, health, and justice services; personal health; the attributes of different places; interpersonal networks; and how mobility is socially differentiated. However, the extent to which these factors shape homelessness and inter‐regional mobilities is unclear. Addressing this gap, I explore 612 people's moves using data collected from five Canadian cities. By analyzing participants' inter‐regional moves over ten years, I identify ten themes of homeless inter‐regional mobility in Canada including: interpersonal networks, the attributes of different places, labour markets and personal finances, the use of movement for personal growth, health and social services, residential mobilities, legal and health institutions, substance abuse and dependence, personal security, and travel. I find that the structures, institutions, resources, and personal experiences that produce homelessness simultaneously push people between places. Amidst an increasing emphasis aimed at understanding homeless experiences in Canada, this paper provides an overview of the inter‐regional mobilities of people experiencing homelessness in Canada.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.300

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.007
Science and technology studies0.0170.004
Scholarly communication0.0040.001
Open science0.0020.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.043
GPT teacher head0.297
Teacher spread0.254 · 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 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

Citations9
Published2020
Admission routes4
Has abstractyes

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Same venueCanadian Geographies / Géographies canadiennesSame topicHomelessness and Social IssuesFrench-language works237,207