Bibliographic record
Abstract
The promising agenda of EU-Russia cooperation has resulted in mutual frustration manifested in continuous, paradoxical crises and isolation between the partners. This article offers a possible way to reflect on an uneasy EU-Russia relationship. In this study, I make problems in EU-Russia cooperation discursively visible by scrutinizing the official speech acts articulated in EU-Russia political and security discourse. I demonstrate that these official speech acts create conditions for a responsive dialogue and, eventually, form a set of prevalent discursive practices that re-produce and reinforce problems in EU-Russia cooperation. Blending Bakhtin‟s dialogic analysis and Onuf‟s constructivist accounts, I strike a balance between theoretical and empirical analyses and develop a model for understanding current and possible future events in the EU-Russia partnership. This model of international cooperation can be transferable beyond its borders to similar examples of relationships currently existing all over the world. Full text available at: https://doi.org/10.22215/rera.v6i1.206
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 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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.028 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".