MétaCan
Menu
Back to cohort
Record W2476248150 · doi:10.1057/9780230801349_6

The European Neighbourhood Policy: a Strategy for Security in Europe?

2007· book-chapter· en· W2476248150 on OpenAlexaff
Stefan Gänzle

Bibliographic record

VenuePalgrave Macmillan UK eBooks · 2007
Typebook-chapter
Languageen
FieldSocial Sciences
TopicEuropean Union Policy and Governance
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsResizingEuropean Neighbourhood PolicyEuropean unionGeopoliticsPolitical scienceTreatyNeighbourhood (mathematics)Context (archaeology)Foreign policyEuropean integrationInternational tradeEconomyPolitical economyDevelopment economicsGeographyPoliticsEconomicsLaw

Abstract

fetched live from OpenAlex

The 2004 enlargement of the European Union (EU) was heralded as ‘historic’ in terms of both its magnitude and geopolitical outreach, yielding the Central and East European countries’ ultimate ‘return to Europe’. Enlargement, however, resulted in more than the mere addition of ten new member states. It also pushed the EU much closer towards what is broadly conceived as a ‘new neighbourhood’ and into an area that the EU considers to be of paramount importance for security in Europe. The future of EU engagement in its neighbourhood will depend on two decisive factors. First, the EU is in an uncertain and difficult period of internal adjustment and consolidation after enlargement and the failed referenda in France and the Netherlands on the Treaty Establishing a Constitution for Europe. Second, the EU is about to absorb the impact that new members such as Poland and the Baltic states (Estonia, Latvia and Lithuania) will have on the EU’s foreign policy towards Eastern Europe (EU Eastern Policy 1 ). It is in this context that the EU is compelled to devise a strategy for the ‘new neighbourhood’ countries, in particular Russia, Belarus, Ukraine and Moldova.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.009
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.006
Scholarly communication0.0090.008
Open science0.0010.004
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0070.002

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 head0.045
GPT teacher head0.311
Teacher spread0.266 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2007
Admission routes1
Has abstractyes

Explore more

Same venuePalgrave Macmillan UK eBooksSame topicEuropean Union Policy and GovernanceFrench-language works237,207