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Record W4392547711 · doi:10.17645/up.7642

Decentralization in Ukraine: Reorganizing Core–Periphery Relations?

2024· article· en· W4392547711 on OpenAlexaff
Sophia Ilyniak

Bibliographic record

VenueUrban Planning · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicUrbanization and City Planning
Canadian institutionsYork University
Fundersnot available
KeywordsDecentralizationCore (optical fiber)Economic systemPolitical scienceEconomicsComputer science

Abstract

fetched live from OpenAlex

This article seeks to determine whether (and how) Ukraine’s Decentralization Reform is reorganizing core-periphery relations. Involving a profound rescaling and reterritorialization of the nation-state, the reform is widely considered one of the most transformational policies of the three decades of the country’s independence and is credited with fostering local self-governance and motivating resistance in the war with Russia. However, such emancipatory ideals promoted by Western institutions and reflected in urbanist literature are contradicted by ongoing economic restructuring—austerity, privatization, and deregulation—where the devolvement of responsibility has placed Ukrainian localities into the competitive environment of place entrepreneurialism. The article outlines how the Decentralization Reform’s attempts to address uneven geographical development are instead reproducing unevenness across local, national, and global scales and advancing the (re)production of neoliberal capitalist space. The global philanthropic project of rebuilding Ukrainian cities in the face of imperial war is intensifying this dynamic, making Ukrainian (sub)urban space an important site for exploring alternatives within and beyond the post-Soviet condition.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0040.002
Open science0.0000.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.044
GPT teacher head0.334
Teacher spread0.290 · 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 designObservational
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

Citations3
Published2024
Admission routes1
Has abstractyes

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