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Record W2143167311 · doi:10.1111/1468-2427.12254

Thinking Through Dualisms in Urban Policy Mobilities

2015· article· en· W2143167311 on OpenAlexaff
Eugene McCann, Kevin Ward

Bibliographic record

VenueInternational Journal of Urban and Regional Research · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicPolicy Transfer and Learning
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMobilitiesSociologyEconomic geographyPositive economicsUrban policyPolitical scienceSocial scienceGeographyEconomicsUrban planningCivil engineering

Abstract

fetched live from OpenAlex

Abstract The growing use of the notion of ‘policy mobilities’ to conceptualize how policy is made and moved across and among cities and urbanized regions has led to worthwhile insights, but has also encouraged some critiques. Many of these address certain dualisms that seem to undergird the policy mobilities approach. This essay engages with three of these apparent dualisms—success/failure, presence/absence and mobilities/immobilities—and argues that while they must be treated with care, they should not be dismissed or expunged a priori. Rather, we argue that there is utility in conceptualizing urban policy mobilities through relational dyads, rather than oppositional dualisms. If studies of policy mobilities, urban or otherwise, are to maintain their momentum, success, failure, presence, absence, mobilities and immobilities should be understood as being intertwined, mutually constituting and reinforcing elements of policymaking.

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)0.012
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0060.070
Scholarly communication0.0160.026
Open science0.0020.017
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0070.001

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 head0.261
GPT teacher head0.500
Teacher spread0.239 · 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 designTheoretical or conceptual
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

Citations107
Published2015
Admission routes1
Has abstractyes

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