Determinants of cross‐border commuting: Do cross‐border commuters within the household matter?
Bibliographic record
Abstract
Cross‐Border commuting is an important form of spatial labor mobility. It is influenced by socio‐economic characteristics and personal attitudes, as well as, by the institutional framework shaped by the labor market, social insurance, and tax laws of the jurisdictions involved. In this paper we analyze the determinants of cross‐border commuting, focusing on the question, whether the existence of cross‐border commuters within the household changes the probability for cross‐border commuting for other household members. The empirical analysis is based on face‐to‐face interviews with employees in the Austrian Land of Vorarlberg, a region with a strong cross‐border commuting tradition especially to Switzerland and Liechtenstein. The sole existence of cross‐border commuters does not change the probability to be a cross‐border commuter. However, we find a significant effect if we interact the existence of cross‐border commuters with the presence of children in the household. Besides this, we present evidence on the role of other socio‐economic and personal characteristics on the cross‐border commuting decision.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".