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Record W2607950920 · doi:10.1080/08865655.2016.1267585

A European Perspective on Anglo-Scottish Cross-border Cooperation: Lessons from EU-funded Territorial Cooperation Programs

2017· article· en· W2607950920 on OpenAlexvenueno aff
Claire Colomb

Bibliographic record

VenueJournal of Borderlands Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCross-Border Cooperation and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsCross-border cooperationPerspective (graphical)Political scienceRegional scienceInternational tradeBusinessSociologyComputer science

Abstract

fetched live from OpenAlex

The article aims to reflect on the development and prospects of cross-border cooperation between Scotland and England in a European perspective. Over the past 25 years the EU has supported specific programs of cooperation across the EU’s internal borders (INTERREG), which have allowed thousands of local and regional actors to work on common actions, projects or strategies to overcome long-standing processes of conflict, competition or lack of cooperation. The paper first discusses the added-value and shortcomings of these EU territorial cooperation initiatives, before considering recent developments and future options for cooperation across the Anglo–Scottish border. In capturing how the drive for local and regional actors within the EU to engage in trans-boundary cooperation is shaped by both the a priori existence of strong, historically-rooted cross-border relationships and by more pragmatic concerns to access new resources and policy ideas, the article goes on to examine how such motivations have played out across the Anglo–Scottish border. While acknowledging the benefits of trans-boundary co-operation, the article provides a more cautious assessment of the various barriers and asymmetries that can hinder cross-border co-operation and, in focusing on the area of spatial planning, highlights a particular challenge for economic and social collaborations across the Anglo–Scottish border. The article ends with a brief reflexion on the implications of the results of the 2016 Brexit referendum, before concluding with the most relevant lessons from European territorial cooperation initiatives for Anglo–Scottish cross-border cooperation.

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)0.011
metaresearch head score (Gemma)0.005
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 score0.059
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.012
Scholarly communication0.0110.006
Open science0.0010.009
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.063
GPT teacher head0.471
Teacher spread0.408 · 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

Citations9
Published2017
Admission routes1
Has abstractyes

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