NATO enhanced forward presence in the Baltics: The nexus between the host and the framework nation
Bibliographic record
Abstract
Following the events in Ukraine in 2014, North Atlantic Treaty Organization decided to strengthen its presence in three Baltic States (3B) by establishing an enhanced Forward Presence (eFP) in Estonia, led by the United Kingdom; Latvia, led by Canada; and Lithuania, led by Germany. This study examines the nexus between host nations (HNs) and the eFP framework nations (FNs) while referencing small state theories. The case study considered theoretical and analytical approaches, including classical realism, neorealism, constructivism, liberal theory, neoliberal theory, shelter theory, alliance theory, alliance shelter theory, theory of the free-riding concept of bandwagoning, strategic hedging, and the concept of neutrality to indicate small states’ behaviour and attitude towards bigger states. The more intensive nexus between FNs and HNs was evident in the 3B; however, it varied when analysing activities in military and economic fields. Empirical evidence related to the FN–HN states’ pair led to different theoretical considerations. The study’s outcome suggests that an individual bespoke approach towards the 3B’s is required. The alliance and alliance shelter theories should be regarded as the most appropriate, albeit not explicitly corresponding with first-hand findings.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".