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Record W2038982642 · doi:10.1177/0096144206297148

Where will the People Go

2007· article· en· W2038982642 on OpenAlex
Kevin Brushett

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Urban History · 2007
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsRegentPublic housingSlumAllotmentEconomic shortageEconomic growthWelfarePublic administrationAffordable housingPolitical scienceGovernment (linguistics)SociologyEconomicsLawPopulation

Abstract

fetched live from OpenAlex

In the late 1940s and early 1950s, Canadian cities dealt with a growing housing shortage while the federal and provincial governments argued over who would implement the provisions of the 1944 National Housing Act. This was particularly true in Toronto. As Torontonians celebrated the construction of Regent Park, Canada's “Premier Slum Clearance and Public Housing Project,” nearly 1,350 Toronto families were housed in dilapidated old army barracks and staff houses. Until Regent Park, the shelters were Toronto's only rent-geared-to-income housing project. This article challenges the assumptions that Toronto's homeless were “shiftless welfare bums” and examines the strategies shelter residents used to survive the often brutal conditions in which they lived and how they hoped to escape them. Finally, it argues that the inability of municipalities to replace emergency shelters with decent affordable housing reveals the long-standing reluctance of Canadian governments to develop social-housing programs to eliminate homelessness.

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.

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)0.002
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.443
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.350
Teacher spread0.314 · 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