Commuting to a Familiar Foreign Country: An Analysis of Enhancers for Cross-Border Commuting from Southern Slovakia to Hungary
Bibliographic record
Abstract
This article is a study of cross-border commuters between Slovakia and Hungary, an area with experience of border changes. Many inhabitants have common characteristics such as ethnic identity and language on both sides of the border. Previous literature suggests that these commonalities are related to “familiarity” with the other side of the border, which results in cross-border commuting. In this study of Slovakian Komárno residents, we focus on the previous experience of staying on the other side of the border as a component of “familiarity,” an enhancer for cross-border commuters. The results of a comprehensive deliberation of these factors that constitute “familiarity,” together with other individual characteristics, suggest that it is the previous experience of staying at the cross-border commuting destination (in Hungary) which leads to actual cross-border commuting, and ethnic identity and use of a common language might not have a large effect on the choice of workplace as far as our data are concerned.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".