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Record W2757191756

National Urban Policy : A Roadmap for Canadian Cities

2016· article· en· W2757191756 on OpenAlexaboutno aff
Abigail Friendly

Bibliographic record

VenueTSpace (University of Toronto) · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsNational PolicyGovernment (linguistics)Urban policyPublic administrationPolitical scienceUrban planningNational governmentChristian ministryPublic policyInstitutionEconomic growthRegional scienceGeographyPoliticsEconomics
DOInot available

Abstract

fetched live from OpenAlex

Over the past 50 years, interest in a national urban policy in Canada has waxed and waned. Although the 1960s represented a high water mark in terms of creating national institutions on urban issues, efforts to develop a national urban policy languished until the early 2000s.The 21st century has seen a renewed interest internationally in national urban policies. This paper draws on the experience of countries that have explicitly pursued national urban policies to solve complex and interrelated urban challenges: the United Kingdom, Australia, Germany, Brazil, and France. It is unclear whether Canada will establish a similar policy or institution. If it does, however, this paper proposes three elements for a national urban policy: Collaborative governance involving cities as joint partners in deciding their fates with the provinces and federal government. Coordinating the diverse policies that affect the quality of life of Canadians living in cities. Robust policy, research, and monitoring mechanisms to identify what is working and best practices both nationally and internationally.

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)0.009
metaresearch head score (Gemma)0.011
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.715
Threshold uncertainty score0.829

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.011
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0090.011
Science and technology studies0.0220.005
Scholarly communication0.0180.008
Open science0.0040.010
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0340.004

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 head0.019
GPT teacher head0.264
Teacher spread0.244 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

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Same venueTSpace (University of Toronto)Same topicCanadian Policy and GovernanceFrench-language works237,207