Migration and Old Age: Japanese Women Growing Older in British Society
Bibliographic record
Abstract
In the article “Migrants, partner selection and integration: crossing borders?” Erna Hooghiemstra analysis why so many Dutch Turks and Moroccans who have spent their youth or their young adulthood in the Netherlands, have chosen to marry a partner who still lives in the country of origin. The objective is to explore the extend to which the high rate of transnational marriages can be explained by (a lack of) integration on the one hand or by factors that are usually put forward as influencing partnerselection - such as the opportunity to meet, the structure and character of the social network and individual processes of rational choice - from the other hand. The statistical comparison between those Turkish and Moroccan who married a so called marriagemigrant and those who married a partner from the Netherlands shows that the two groups differ significantly from each other. Also: the motives of men and women to marry across the border seem to be very distinct. Some differences between the two types of partnerchoices can be explained by integration theories others by general partnerchoice theories. The general conclusion is that understanding of the partnerchoice of migrants goes beyond the boundary of knowlegde of integration processes as well as general processes of partnerselection. The important implication is that integration alone can’t explain the partnerchoice of migrants and that a general perspective on partnerchoice without considering the specific background of migrants is too limited to understand the partnerchoice of migrants.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".