Transnational Infancy: A New Context for Attachment and the Need for Better Models
Bibliographic record
Abstract
Abstract Researchers have paid little attention to the effects of a rapidly globalizing world on infants and toddlers, even though some features of globalization may have a significant impact on their development and well-being. For example, fragmentation occurs in many North American and European transnational families when infants are separated from parents and cared for by geographically distant relatives, as is the case when new immigrants temporarily leave their infants in their country of origin or send them back to be cared for by relatives. There is much reason to believe that such separations can have an adverse effect on attachment, the emotional development of children, and the adjustment of parents. Yet Western mental-health models may not accurately capture the full complexity of these new realities, nor adequately address risk and resiliency factors in clinical contexts. This article argues that it is the time to devote attention to the experience of infants and toddlers who exist in transnational environments, as these very young children may well be the most overlooked participants in globalization. This article proposes a model to support an emergent field of research, policy making, and practice.
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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 | 0.017 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.055 |
| Scholarly communication | 0.011 | 0.020 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".