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Record W3120740743 · doi:10.1177/1078087420984241

Beyond Neoliberalism: A Policy Agenda for a Progressive City

2021· article· en· W3120740743 on OpenAlexaff
Meghan Joy, Ronald K. Vogel

Bibliographic record

VenueUrban Affairs Review · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsToronto Metropolitan UniversityConcordia University
Fundersnot available
KeywordsNeoliberalism (international relations)PoliticsEconomic growthUrban policyNoticeInequalityPolitical scienceUrban politicsUrbanizationAffordable housingUrban planningPublic administrationPolitical economyDevelopment economicsSociologyEconomicsLaw

Abstract

fetched live from OpenAlex

The urban crisis—poverty and inequality, un—and under-employment, inadequate and unaffordable housing and public transportation, pollution and climate disasters—is the result of the failure of the neoliberal agenda to produce adequate funds and capacities to ensure the provision of services necessary for the city to function and its residents to thrive, especially the most vulnerable, and increasingly, the middle class. In the last few years, there appears to be a potential for a new more radical direction in urban policy. Yet, urban scholars and practitioners have been slow to notice the new possibilities that reopens the question of whether cities may engage in redistributive policies. In reviewing the history and current practice of progressive politics and policy in cities, this paper explores what a policy agenda for a progressive city might entail and identifies themes and questions for a renewed urban politics research agenda.

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)0.008
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: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0050.023
Scholarly communication0.0140.013
Open science0.0010.008
Research integrity0.0110.011
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 head0.045
GPT teacher head0.275
Teacher spread0.229 · 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
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

Citations39
Published2021
Admission routes1
Has abstractyes

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