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Record W4313389721 · doi:10.54825/zxlp1314

Tent encampments in Toronto, Canada: Excavating Northern housing informalities

2022· article· en· W4313389721 on OpenAlexaboutno aff
Allison Evans

Bibliographic record

VenueRadical Housing Journal · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsEnforcementUrbanizationState (computer science)PopulationHuman settlementGeographyEconomyPolitical scienceEconomic geographyEconomic growthSociologyEconomicsLawArchaeologyDemography

Abstract

fetched live from OpenAlex

This paper examines the ambiguities of municipal state regulation in relation to the dwelling practices of Toronto’s unhoused population. This paper argues tent encampments are a persistent mode of urban informality in the global North, where tents and other small structures provide a source of housing, particularly in cities with limited housing options. Using the City of Toronto as a case study, this paper analyzes how urban informality is reproduced and mediated by state policies, protocols, and actors. The findings suggest the local state—at times ambiguous and negotiated relative to an array of actors, property relations, and desirable formalities—routinely clears encampments from public property. The city’s enforcement and regulatory regime often removes tent encampments without rehousing people, thus contributing to cyclical patterns of informal urbanization. The paper concludes with recommendations for future research to better understand the similarities, differences, and nuances of this mode of urban informality in global North cities and to open the regulatory and policy field to options beyond criminalization.

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, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.798
Threshold uncertainty score0.999

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 studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.035
GPT teacher head0.357
Teacher spread0.322 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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