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Record W4416248127 · doi:10.1145/3764687.3769917

Designing Shared Cultural Activities to Connect Generations: A Scoping Review

2025· article· W4416248127 on OpenAlexaff
Sajini Lankadari, Beheshteh Atrian, Bernd Ploderer, S. Desai, Yuehao Wang, Alethea Blackler

Bibliographic record

Venuenot available
Typearticle
Language
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsYork University
Fundersnot available
KeywordsKey (lock)Embodied cognitionIncentiveCultural diversityAffordance

Abstract

fetched live from OpenAlex

As geographically dispersed families become increasingly common, digital technologies have emerged as a vital means of supporting intergenerational shared activities. Cultural elements such as oral traditions, crafts, or festivals are often integrated into shared activities as key components for fostering intergenerational connection and transmitting family memories and values. However, in existing research, culture is frequently referenced in broad and ambiguous terms. Therefore, the aim of our study is to clarify the types of intergenerational shared cultural activities, their sharing mechanisms, and the role of digital technology in supporting them. This paper reviews 48 relevant publications from 2000 to 2025. Through our analysis, we propose future design opportunities, including expanding interaction approaches for material and embodied cultural activities in geographically dispersed families; designing incentive mechanisms that support diverse family role dynamics; and introducing interpretive support at key moments of shared cultural activities to help technology convey and mediate cultural meanings.

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)0.033
metaresearch head score (Gemma)0.090
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.033
Threshold uncertainty score0.177

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.090
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0250.023
Science and technology studies0.0020.003
Scholarly communication0.0070.008
Open science0.0030.004
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.070
GPT teacher head0.385
Teacher spread0.315 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations2
Published2025
Admission routes1
Has abstractyes

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