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Record W2300509040 · doi:10.3138/chr.3265

Urban Renewal Revisited: Toronto, 1950 to 1970

2016· article· en· W2300509040 on OpenAlexvenueaboutno aff
Richard White

Bibliographic record

VenueCanadian Historical Review · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicUrbanization and City Planning
Canadian institutionsnot available
Fundersnot available
KeywordsInterpretation (philosophy)Urban planningAction (physics)SociologyConflationPrivate propertyUrban policyHistoryPolitical scienceLawCivil engineeringEngineeringEpistemology

Abstract

fetched live from OpenAlex

Postwar programs of urban renewal in Canadian cities have long been considered failures in the sense that their objectives were faulty and their impacts generally harmful. However, so complete is the consensus around this interpretation that historians have not made as much effort as they might have to understand the goals and mechanisms of renewal programs. This close study of postwar urban renewal in Toronto identifies several significant aspects, largely unrecognized, of one city's renewal program. It clarifies that urban renewal and public housing, though often conflated, were actually two discrete things. It finds that renewal advocates carefully inventoried the communities they sought to renew – their plans were by no means based on James C. Scott's now paradigmatic “synoptic” view – but it confirms that many did indeed have insufficient understanding of those communities. It also finds that much less urban renewal was done in Toronto than is generally assumed, suggesting that urban renewal's failure resulted more from inaction than from action. In conclusion, it notes that physical renewal of the city was ultimately accomplished not by urban renewal programs but, rather, by the actions of private property owners and entrepreneurs, raising questions about public endeavour as a means of urban improvement.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.267
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.031
GPT teacher head0.284
Teacher spread0.252 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations7
Published2016
Admission routes2
Has abstractyes

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