Bridging Communication Gaps Across Generational & Cultural Divides Among Chinese-Canadian Families & Communities
Bibliographic record
Abstract
Intergenerational relationships are becoming increasingly important, as people are living longer and thus spending more time with people from different generations. Despite the growth in the area of research on intergenerational relationships and communication, it is largely lacking in historical and cultural context. Few have explored cultural differences in values, behaviour, and identity in intergenerational conflict and cross-cultural communication. Furthermore, little is known about intergenerational communication, conflict, and coping within the context of Eastern cultures. \nThe purpose of this study is to better understand the nature of intergenerational communication and conflict among Chinese-Canadian families, the existing strategies used to manage conflict, and the impacts of effective intergenerational communication on the lives of older and younger Chinese-Canadians. Through listening and learning from Chinese-Canadians across four generations and a community of experts, areas of support and needs were identified and incorporated into the design process. The analysis shows a strong correlation between age, history, migration, social environments, and communication behaviours. Overall, the results highlight the complex roles of culture, history, and trauma in communication among multi-generational Chinese-Canadian families. \nA game-based approach is proposed to promote understanding between Chinese-Canadians across generations through empathic communication and storytelling. The artifact aims to connect game enjoyment and intergenerational perceptions and communication and serves as an inspiration piece to foster positive intergenerational bonds. \nThe efforts of this research are an expression of commitment by the individuals and organizations dedicated to supporting Chinese-Canadian communities to foster social spaces that celebrate diversity and inclusion.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".