Re-Evaluating the EU’s Engagement with its Eastern Neighbourhood: A Relationality Perspective
Bibliographic record
Abstract
The call to re-evaluate the EU’s foreign policy engagement from the perspective of relationality is becoming commonplace. However, we still lack conceptual clarity on the notions of relation(s) and relationality. This article argues that to better understand relationality in International Relations and EU studies, we should conceptually differentiate between the two frames of reference – the conceptualisation of relationality grounded in positivist thinking and the conceptualisation of relationality anchored in complexity-thinking. Drawing on the Relational Sociology, particularly, critical realism by Pierpaolo Donati and Margaret Archer, we further operationalise relationality and highlight three relational modes of me-ness, thee-ness and we-ness. Applying the operationalisation to the EU relations with the six Eastern Partnership states and Russia, we trace the development of the relations and identify relational patterns. We find that the EU and its partners only engaged in hierarchical transactional-logic relations, being unable to develop what Donati and Archer call a genuine we-relation. Our findings also point to the fact that the positivist-based interpretation of relationality has prevailed, with the EU’s unsuccessful attempts to adapt its mode of relational engagement to the world of complexity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.022 |
| Scholarly communication | 0.016 | 0.015 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".