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Record W6945876924

Multiple Barriers: The Multilevel Governance of Homelessness in Canada

2022· article· en· W6945876924 on OpenAlexaboutno aff

Bibliographic record

VenueTSpace · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate governanceKey (lock)Service (business)Participant observationCoproduction
DOInot available

Abstract

fetched live from OpenAlex

Despite decades of efforts to combat homelessness, many people continue to experience it in Canada’s major cities. There are a number of barriers that prevent effective responses to homelessness, including a lack of agreement on the fundamental question: what is homelessness? In Multiple Barriers, Alison Smith explores the forces that shape intergovernmental and multilevel governance dynamics to help better understand why, despite the best efforts of community and advocacy groups, homelessness remains as persistent as ever. Drawing on nearly 100 interviews with key actors in Vancouver, Calgary, Toronto, and Montreal, as well as extensive participant observation, Smith argues that institutional differences across cities interact with ideas regarding homelessness to contribute to very different models of governance. Multiple Barriers shows that the genuine involvement of locally based service providers, with the development of policy, are necessary for an effective, equitable, and enduring solution to the homelessness crisis 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 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 categoriesInsufficient 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 score0.496
Threshold uncertainty score0.999

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 studies0.0010.000
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 head0.038
GPT teacher head0.372
Teacher spread0.334 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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