Beyond the GenerAsians : Intergenerational programming and Vancouver’s Chinatown
Bibliographic record
Abstract
Applying the "age" lens, this paper asks: how can intergenerational programming move the current Vancouver Chinatown Revitalization process towards a more ageintegrated and life course-oriented approach? In addition, a meta-question is: How can intergenerational programming assist diverse populations (i.e. younger and older people) collectively search for new meanings for Chinatowns in transition? The qualitative and quantitative methods used in this research include reviewing literature, primary documents, city documents, unpublished works, and conference papers. Basic demographic analyses, community interviews, and surveys were conducted. As a member of the Vancouver Chinatown Revitalization Committee and intern at the City of Vancouver, personal observations were also made between 2002 and 2004. This research adopts the Community for all Ages model to evaluate Vancouver's Chinatown revitalization process and makes recommendations that move it towards intergenerational programming - a mechanism to respond to key challenges from the "age lens": changing age demographics, the diversifying Chinese-Canadian community in Vancouver, and aging institutions in Chinatown. Challenging traditional theories of generations and assimilation, the results of this research illustrate the need for planners, policymakers, and community workers to recognize the diverse stories and experiences along the age continuum and to adopt a life-course approach in moving communities from age-segregation to age-integration. Identifying some key issues for implementation and future research, this study has implications for the application of intergenerational programming in Vancouver's Chinatown but also in other Chinatowns currently facing similar challenges.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".