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Record W2105037343

The State of Homelessness in Canada 2013

2013· article· en· W2105037343 on OpenAlexaboutno aff
Stephen Gaetz, Jesse Donaldson, Tim Richter

Bibliographic record

VenueYork University Digital Library (York University) · 2013
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsState (computer science)Political scienceHousing FirstCriminologySociologyPsychologyComputer sciencePsychiatryMental health
DOInot available

Abstract

fetched live from OpenAlex

Canada is nearing an important crossroads in our response to homelessness. Since homelessness emerged as a significant problem – in fact, as a crisis – in the 1990s, with the withdrawal of the federal government’s investment in affordable housing, communities have struggled to respond. Declining wages (even minimum wage has not kept up with inflation in any jurisdiction in Canada), reduced benefit levels–including pensions and social assistance—and a shrinking supply of affordable housing have placed more and more Canadians at risk of homelessness. For a small, but significant group of Canadians facing physical and mental health challenges, the lack of housing and supports is driving increases in homelessness. Prevention measures – such as ‘rent banks’ and ‘energy banks’ that are designed to help people maintain their housing – are not adequate in stemming the flow to homelessness. The result has been an explosion in homelessness as a visible and seemingly ever present problem.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.131
Threshold uncertainty score0.954

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0100.003
Scholarly communication0.0040.001
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.000

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 head0.013
GPT teacher head0.210
Teacher spread0.197 · 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

Citations85
Published2013
Admission routes1
Has abstractyes

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