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Record W3107356218 · doi:10.1177/0096144220976127

The Life, Death, and Legacy of the Toronto Bureau of Municipal Research, 1914-1983

2020· article· en· W3107356218 on OpenAlexaffabout
Gabriel Eidelman, Maya Hoke

Bibliographic record

VenueJournal of Urban History · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDemiseWork (physics)CitizenshipPublic administrationGovernment (linguistics)Local governmentPolitical scienceSociologyLawPoliticsEngineering

Abstract

fetched live from OpenAlex

The Toronto-based Bureau of Municipal Research published over 800 bulletins and reports on urban issues in Canada between 1914 and 1983. Much has been written about its parent organization, the New York Bureau of Municipal Research. But the history of the Toronto chapter has all but been ignored. This article is a step toward understanding the history of the Toronto Bureau, and its impact on urban policy and local government in the Greater Toronto area. The article proceeds in three parts. First, we tell the story of the Bureau’s genesis, the evolution of its mission and leadership over time, and its eventual demise. Next, we analyze the Bureau’s body of work, identifying two common themes—efficiency and informed citizenship—found across the complete catalog of Bureau documents housed at the City of Toronto Archives. Finally, we examine the Bureau’s tangible achievements, most apparent in areas of municipal finance and administrative reform in the 1910s, 1920s, and 1930s, as well as the Bureau’s enduring legacy, including the lessons its work holds for modern-day urban policy debates in Greater Toronto and elsewhere.

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.977
Threshold uncertainty score0.942

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.011
Science and technology studies0.0230.013
Scholarly communication0.0100.002
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.094
GPT teacher head0.318
Teacher spread0.224 · 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.

Study designQualitative
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

Citations2
Published2020
Admission routes2
Has abstractyes

Explore more

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