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Record W4412525255 · doi:10.1111/ciso.70015

The Disappearance of Urban Horses and the Rise of Homelessness and Mental Illness

2025· article· en· W4412525255 on OpenAlexaffabout
Vincent Laliberté

Bibliographic record

VenueCity & Society · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsMental illnessPsychologyPsychiatryMedicineMental health

Abstract

fetched live from OpenAlex

ABSTRACT Homelessness is growing in cities across the Western world, accompanied by high rates of mental health problems. To address this crisis, programs focus on providing affordable housing and mental health services. Yet this effort seems insufficient to stem the tide. Based on long‐term ethnographic research with horse‐drawn carriage drivers in Montreal, I tell the story of Jerome, who was experiencing homelessness and psychic distress prior to his unexpected encounter with a horse‐drawn carriage. To understand how Jerome reoriented his life, I build on the urban literature on convivial spaces while also drawing on multispecies ethnography's attention to entanglements with non‐human animals. I argue that Jerome benefitted from the “atmosphere of conviviality” of the carriage stand, where horses foster spontaneous interactions, encourage lingering and enjoyment, and facilitate connections across social divides. Encounters in convivial atmospheres may also allow people to build routines and even craft a way of life. This research brings a view of homelessness and mental illness as a process entangled with the urban ecology. The transformation of the city, particularly the disappearance of domestic animals such as horses, may be an overlooked yet significant factor in the rise of unhoused people with psychiatric conditions caught in the institutional circuit.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.292
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.017
GPT teacher head0.354
Teacher spread0.337 · 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 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

Citations0
Published2025
Admission routes2
Has abstractyes

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