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Record W3091242290 · doi:10.17645/up.v5i3.3679

Planning for Local Economic Development: Research into Policymaking and Practice

2020· article· en· W3091242290 on OpenAlexaff
Evan Cleave, Godwin Arku

Bibliographic record

VenueUrban Planning · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional Economics and Spatial Analysis
Canadian institutionsWestern UniversityToronto Metropolitan University
Fundersnot available
KeywordsZoningUrban planningProsperityVulnerability (computing)Corporate governancePolitical scienceEconomic growthLocal economic developmentEnvironmental planningRegional scienceSociologyGeographyEconomicsEngineeringManagement

Abstract

fetched live from OpenAlex

This thematic issue of Urban Planning brings together a collection of seven articles that explore and critically engage with contemporary issues with local economic development and connect with the broader fields of urban development and planning. The articles presented here provide a complementary mix of broader conceptualizations and research and narrower case-studies which draw from a range of geographies. Contributions include the development and application of a vulnerability and risk measures for economic prosperity; examinations of how urban planning and zoning are used as tools to address industrial decline and spur new forms of economic production; complementing investigations into the role of innovation within local economic development examining the role of public and private institutions as well as broad and targeted policy interventions; and the relationship between ‘big-tech,’ economic development and urban planning and governance.

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)0.022
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.037
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.011
Science and technology studies0.0070.022
Scholarly communication0.0250.016
Open science0.0030.009
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0250.003

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 head0.194
GPT teacher head0.351
Teacher spread0.157 · 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 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

Citations1
Published2020
Admission routes1
Has abstractyes

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