The Schengen Crisis and the End of the “Myth” of Europe Without Borders
Bibliographic record
Abstract
The European Schengen crisis, spurred off by a wave of terrorist attacks in Europe and an unexpected increase in migration across the Mediterranean Sea in 2015 led to a re-questioning of the functions of borders in European integration. The ideal of a “Europe without borders” has been particularly affected. Indeed, the re-introduction of border controls in several Member States of the European Union (EU) symbolized a new obstacle to free circulation in Europe and the “separation” function of the border seems to have strengthened. This contribution will argue that the Schengen crisis has not put an end to “Europe without borders” in terms of free movement of goods, services, capital and people. It will claim instead that there has been a construction of a “myth” of “Europe without borders” with a different meaning, i.e. in which “Europe without borders” is not a means to an objective but an objective in itself, that of an EU where all borders are assumed to have negative functions and should therefore disappear. The Schengen crisis helps to unravel this “myth” by demonstrating that borders can also have positive functions, that they persist within the EU and that their control remains a competence of the EU Member States. Adopting a less mystified view of “Europe without borders” and assessing its origin and development from a disciplinary approach in Contemporary History, helps to better explain the processes of de- and re-bordering in Europe and their relationship to European integration.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.019 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| 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".