(Un)Familiarity? Labor Related Cross-Border Mobility in Sønderjylland/Schleswig Since Denmark Joined the EC in 1973
Bibliographic record
Abstract
This article presents an analysis of recent developments in labor-related mobility (cross-border commuting) in the Danish–German border region of Sønderjylland-Schleswig. The region had an integrated labor market, until today's German–Danish border was drawn in 1920, dividing the historic Duchy of Schleswig. Until Denmark joined the EC in 1973, the Danish–German border was practically closed to labor-related mobility. Since then, commuting remained at very low levels until the mid-2000s, even though unemployment figures north and south of the border developed unevenly, and two national minorities had strong social and cultural ties across the border. From about 2005–2008 there was a drastic increase in commuting from Germany to Denmark, while commuting in the other direction has remained at a very low level. Here, the article comes up with some explanations for this development using the concept of (Un)Familiarity as developed by Bas Spierings and Martin van der Velde.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".