Participatory Design for Intergenerational Culture Exchange in Immigrant Families
Bibliographic record
Abstract
Language and cultural barriers critically threaten the social relationships between grandparents and grandchildren in immigrant families. Cultural exchange activities, like shared storytelling, can foster these crucial connections. However, existing barriers make these seemingly routine interactions challenging for families to navigate. The resulting intergenerational drift places grandparents at high risk of sustained social isolation from their families. Past works have presented technology-mediated supports for grandparent-grandchild social interactions in non-immigrant families and have found that these interventions do foster stronger connections in both physically close and distant multigenerational families. We explore how to support the specific needs of immigrant families through Magic Thing participatory design workshops with grandchildren and grandparents together in order to reveal the social interactions that would support their cultural exchange. We use the Magic Thing to move the standard dialogic grandparent-grandchild relationship into a trialogic one, creating space for comfortable social connection and storytelling through the shared creation of the design. We find that technology-mediated support of intergenerational immigrant cultural exchange must be designed for this trialogic process, consider the role of expressing values as a form of meta-commentary on a story, and shift the perspective on existing "barriers" to consider how they might foster further engagement.
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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 | 0.062 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".