MétaCan
Menu
Back to cohort
Record W2626867127 · doi:10.1080/13597566.2017.1343723

Secondary foreign policy activities in Third sector cross-border cooperation as conflict transformation in the European Union: The cases of the Basque and Irish borderscapes

2017· article· en· W2626867127 on OpenAlexfundno aff
Cathal McCall, Xabier Itçaina

Bibliographic record

VenueRegional & Federal Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCross-Border Cooperation and Integration
Canadian institutionsnot available
FundersQueen's UniversityFP7 Socio-Economic Sciences and HumanitiesQueen's University BelfastEuropean Commission
KeywordsInstitutionalisationIrishEuropean unionPolitical scienceEconomyPolitical economyInternational tradeEconomicsLaw

Abstract

fetched live from OpenAlex

This paper provides a comparative examination of Third (non-public, non-profit) sector cross-border cooperation contributing to conflict transformation in the Basque (France/Spain) and Irish (UK/Ireland) borderscapes. The comparison is based on the premise that the European Union (EU) played a different role in both cases. In the Irish case, the EU contributed to the institutionalization of a peace process that included cross-border cooperation between Third sector organizations among its policy instruments contributing to conflict transformation. In the Basque case, the unilateral renunciation of violence by ETA (Euskadi eta Askatasuna) in 2010 did not generate the consistent involvement of the EU in an institutional peace process. However, some Third sector organizations became secondary foreign policy actors using EU instruments for cross-border economic, social, and cultural cooperation between France and Spain in order to reinforce their cross-border networks, which indirectly impacted on conflict transformation.

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)0.007
metaresearch head score (Gemma)0.004
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 score0.029
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0110.009
Scholarly communication0.0100.003
Open science0.0010.007
Research integrity0.0030.002
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 head0.064
GPT teacher head0.430
Teacher spread0.366 · 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

Citations9
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueRegional & Federal StudiesSame topicCross-Border Cooperation and IntegrationFrench-language works237,207