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Record W2021543687 · doi:10.1080/08865655.2009.9695727

The transboundary landscape of the Eu‐Schengen border

2009· article· en· W2021543687 on OpenAlexvenueno aff
Maunu Häyrynen

Bibliographic record

VenueJournal of Borderlands Studies · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicCross-Border Cooperation and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsEuropean unionPolitical scienceMember statesGeographyCzechLegislationResizingEconomyInternational tradeLawBusiness

Abstract

fetched live from OpenAlex

The theme of this dossier of the Journal of Borderlands Studies is the transboundary landscape of the Schengen border. The Schengen border refers to the common external border of those European countries that signed the Schengen Agreement (1985/1990), which in 1999 became integrated in European Union (EU) legislation. The aim of the agreement is to create a zone of free movement, the so-called Schengen area, between the signatories and to harmonize the area's external border-control arrangements. It now comprises most of the EU member countries, excluding the United Kingdom, Ireland, Romania, and Bulgaria but including the non-members Norway, Iceland, and Switzerland. Besides Romania and Bulgaria, the Schengen area currently borders with Russia, Belarus, Ukraine, Turkey, Croatia, Serbia, Macedonia (FYROM), and Albania outside the EU. Russia had become a neighbor of the area in 2001, when Finland joined the agreement. A more dramatic shift took place with the extension of the land area that occurred with the addition of new member states (Estonia, Latvia, Lithuania, Poland, Czech, Slovakia, Hungary, and Slovenia) in December 2007 (see DeBardeleben 2005, 6-8).

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: none
Teacher disagreement score0.008
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.007
Scholarly communication0.0080.005
Open science0.0000.005
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.025
GPT teacher head0.379
Teacher spread0.354 · 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

Citations4
Published2009
Admission routes1
Has abstractyes

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