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Record W4411094394 · doi:10.1111/joes.12708

Multidimensional Regional Development in EU: A Systematic Review

2025· review· en· W4411094394 on OpenAlex
Alexandre Canário Borrega, Conceição Rego, Miguel Rocha de Sousa

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Economic Surveys · 2025
Typereview
Languageen
FieldSocial Sciences
TopicRegional Development and Policy
Canadian institutionsInternational Political Science Association
Fundersnot available
KeywordsEconomicsRegional developmentRegional scienceEconometricsMacroeconomicsGeography

Abstract

fetched live from OpenAlex

ABSTRACT Regional disparities within the EU remain a persistent challenge, demanding comprehensive research. Enhancing cohesion and convergence while promoting sustainability between and within its regions is crucial to addressing these disparities. This study conducts a systematic literature review on regional development in the EU, identifying key determinants and potential sources of these disparities through a multidimensional lens. Using the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses methodology, our database considers 92 papers related to regional development in the EU. Our analysis shows that most studies predominantly focus on economic factors like employment and GDP, and there is an emerging recognition of the necessity to incorporate social and environmental aspects into regional development studies. This study maps the current state of literature and identifies gaps, particularly the need for more multidimensional and holistic approaches on regional development. These findings underscore the importance of a comprehensive approach in future research and policymaking are crucial for addressing regional disparities and promoting sustainable development across the EU regions.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.552
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.114
GPT teacher head0.407
Teacher spread0.292 · 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