MétaCan
Menu
Back to cohort
Record W4412790512 · doi:10.1080/08865655.2025.2539973

Economy and Border Regions – A Research Gap? Results from a Scoping Review

2025· review· en· W4412790512 on OpenAlexvenueno aff
H.G. Balfour Paul, Tobias Chilla, Carola Sommer

Bibliographic record

VenueJournal of Borderlands Studies · 2025
Typereview
Languageen
FieldSocial Sciences
TopicCross-Border Cooperation and Integration
Canadian institutionsnot available
FundersDeutsche Forschungsgemeinschaft
KeywordsPolitical scienceEconomic geographyEconomyEconomic systemEconomicsRegional scienceSociology

Abstract

fetched live from OpenAlex

Borders are a prominent element in economies: international interactions cross at least one border, marking differences in regulation. Classical economics sees borders mainly in terms of transaction costs, which can be decreased through trade liberalization, as illustrated by free trade agreements and the European integration process. More critical approaches reflect on who profits from border regimes and liberalization, and who does not. At the local level, however, knowledge on economic functioning seems to be rather limited, with prominent debates on cohesion, border-related barriers, and resources often being vaguely linked to economic dynamics. Based on a scoping review, this paper aims to enhance this understanding through a systematic overview of the academic discourse on the border-economy-nexus. Our aim is to reveal geographic and sectoral foci as well as conceptual strands in the academic discourse. The results reveal a strong focus on the US–Mexico border and European borders. Topics such as trade, the informal economy and agriculture are primarily addressed. While most existing research considers differentials, barriers and resources, it rarely refers to the border region on a small scale. Based on such arguments, we formulate proposals for a research agenda that more systematically address dynamics within border-regional economies.

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 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)0.005
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.757
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.268
GPT teacher head0.571
Teacher spread0.303 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations4
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Borderlands StudiesSame topicCross-Border Cooperation and IntegrationFrench-language works237,207