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Record W4403373144 · doi:10.1515/9780228022084

Cities and the Constitution

2024· book· en· W4403373144 on OpenAlexaboutno aff

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2024
Typebook
Languageen
FieldSocial Sciences
TopicAmerican Constitutional Law and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsConstitutionPolitical scienceGeographyLaw

Abstract

fetched live from OpenAlex

Canada’s largest cities have faced exponential growth, with the trajectory rising further still. Due to their high density, cities are the primary sites for opportunities in economic prosperity, green innovation, and cultural activity, and also for critical challenges in homelessness and extreme poverty, air pollution, Indigenous-municipal relationship-building, racial injustice, and transportation gridlock. While city governments are at the forefront of mitigating the challenges of urban life, they are given insufficient power to effectively attend to public needs. Cities and the Constitution confronts the misalignment between the importance of municipalities and their constitutional status. While our constitution is often considered a living document, Canada has one of the most complicated amending formulas in the world, making change very difficult. Cities are thus constitutionally vulnerable to unilateral provincial action and reliant on other levels of government for funding. Could municipal power be reimagined without disrupting the existing constitutional structure, or could the Constitution be reformed to designate cities a distinct tier of government? Among other novel proposals, this groundbreaking volume explores the idea of recognizing municipalities in provincial constitutions. The first volume of a complementary pair, authored by renowned Canadian legal and urban studies scholars, Cities and the Constitution suggests contemporary solutions to one of our most pressing policy dilemmas.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.887
Threshold uncertainty score0.409

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0140.016
Scholarly communication0.0100.003
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0140.002

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 head0.016
GPT teacher head0.233
Teacher spread0.217 · 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 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

Citations1
Published2024
Admission routes1
Has abstractyes

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