Grandparents Across the Ocean: Eastern European Immigrants’ Struggle to Maintain Intergenerational Relationships
Bibliographic record
Abstract
Many contemporary immigrants belong to transnational families-families that maintain significant contact with two or more countries. These families identify with multiple environments and deal with life-cycle changes over extensive geographical space. This paper has two major aims: 1) to better understand how today’s immigrant families facilitate intergenerational relationships across significant distances; and 2) to learn more about the understudied population of recent immigrant professionals from Eastern Europe in the United States. To accomplish these aims, in-depth qualitative interviews were conducted with 24 immigrant mothers and fathers from Eastern European countries residing in the United States. Based on grounded theory methodology, we identified four themes: (1) The definition of “family” and the importance of extended family ties: “The relationships are tighter knit than those in the U.S.”; (2) The role of grandparents in childrearing: “Who else do you think is more appropriate?”; (3) The strategies of maintaining intergenerational relationships: “I want my son to know his predecessors’ language”; and (4) The stress of being torn between two worlds: “I don’t want to be happy at the expense of my extended family.” Our findings suggest that, in spite of advances in communication and travel, and a strong desire for continuation of intergenerational relations in immigrant families, emotional transnationalism is not easily achieved.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".