Love Across Borders: On Population Structures, Meeting Places and Preferences in a Globalizing World
Bibliographic record
Abstract
In our paper, we study the factors shaping the formation of four different types of marriage in Switzerland: marriages with a Swiss partner, marriages with partners from the neighboring countries which are geographically proximate and where one of the official languages of Switzerland is spoken, marriages with partners from other European countries and with partners from overseas. Going beyond the current state of research, we study not only the national structural characteristics of the Swiss partner market and the individual resources of the spouses, but the actual meeting places of the partners and their reasons for being in these locations. Thus, we analyze whether, in a globalizing world and partner market, it is still primarily national opportunity structures that shape different forms of intermarriage. Using a mixed-methods approach we first show, based on census data, that the probability of these marriages is shaped by the structural opportunities of the partner market in Switzerland and individual characteristics like age and education. Second, relying on survey information, we demonstrate that bi-national relationships exhibit a specific pattern of meeting places: in particular, those couples with one partner from a non-neighboring or non-European country often meet abroad and in more open foci of activity. This has not previously been demonstrated empirically in the research literature and clearly shows that the factors shaping these marriages are not covered by a theoretical model focusing on the structural opportunities of national societies. Finally, we scrutinize narrative interviews and show that meeting a spouse abroad is the result of both specific partner preferences and patterns of spatial mobility. Thus, global opportunity structures are to a certain degree shaped by individual agency.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".