Bibliographic record
Abstract
In recent years the seemingly firm historical ties between Warsaw and Berlin have become increasingly strained. This results from a growing political asymmetry between the two countries. Germany moved into a semi-hegemonial position under the conditions of the triple crisis of banking, economy and sovereign debt in the eurozone. Consequently, German chancellor Angela Merkel was in a strong enough position to implement ordoliberal reforms of the eurozone’s governance architecture, which were promoted as an approach without alternatives. Merkel maintained her uncompromising stance during the migration crisis in the summer of 2015, when she demanded implementation of compulsory migrant distribution quotas across the EU. Poland and the Visegrád countries had initially strongly supported German leadership in resolving the eurozone crisis. The alienation from Germany’s European agenda however became significant under the conditions of the migration crisis. Here the firm opposition of Poland and the rest of the Visegrád Group towards Germany’s preferences shows a strategic mismatch between the EU’s liberal core, which is spearheaded by Germany, and the concept of the “illiberal” state, which Poland has embraced under the PiS government. The willingness to resolve these differences will be crucial in determining the future shape of Polish-German relations.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".