The Resurrection of Borders Inside of the Schengen Area and its Media Representations
Bibliographic record
Abstract
The bordering processes inside of the Schengen Area are traditionally under the scrutiny of border studies scholars. The European Union has been repeatedly displayed as a laboratory for a free cross-border movement, often with synonyms like an ostensibly borderless area (Scott 2012). This so-called Schengen culture (Zaiotti 2011) developed due to intensifying cross-border contact and integration between EU member states. However, in the decade between 2010 and 2020 this Schengen culture has been repeatedly challenged by the geopolitical crises and nationalistic political narratives and decisions. This study concentrates on this debate about borders in the selected European news. The analysis of news articles from six newspapers (Mladá fronta, Hospodářské noviny, Le Figaro, Le Monde, Der Standard, and Die Presse) shows how the context of the border debate evolved under the impact of migration crises and coronavirus crisis. Throughout the decade of the 2010s, this study witnesses the gradual securitization of borders inside of the EU and illustrates how the symbolic language and various narratives contributed to this development.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".