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Record W3159365872 · doi:10.1145/3449172

Participatory Design for Intergenerational Culture Exchange in Immigrant Families

2021· article· en· W3159365872 on OpenAlexafffund
Amna Liaqat, Benett Axtell, Cosmin Munteanu

Bibliographic record

VenueProceedings of the ACM on Human-Computer Interaction · 2021
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsUniversity of Toronto
FundersAGE-WELL
KeywordsGrandparentSociologyImmigrationStorytellingCitizen journalismPsychologyDevelopmental psychologyNarrativePolitical science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.062
metaresearch head score (Gemma)0.051
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.062
Threshold uncertainty score0.329

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0620.051
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0050.007
Scholarly communication0.0050.003
Open science0.0030.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.001

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.

Opus teacher head0.122
GPT teacher head0.350
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations27
Published2021
Admission routes2
Has abstractyes

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