Future through Memory - Virtual Storytelling in Toronto's Chinatown
Bibliographic record
Abstract
Future through Memory is a study in the affordances of virtual production through co-design as a method of civic engagement, placemaking and placekeeping in Toronto’s Chinatown. The title “Future through Memory” hearkens back to Wendy Chun’s text, The Enduring, Ephemeral, or The Future is a Memory (2008). Using participatory action research as the central methodology, co-creation workshops were held with individuals within the Toronto Chinatown community to develop what Pierre Nora’s describes les lieux de mémoire (site of memory) in "Between Memory and History: Les Lieux de Mémoire" (1998) within an interactive documentary using WebVR (A-Frame). This study explores the use of collective memory, oral testimony, transmedia storytelling and 3D photogrammetric scans as a method to highlight the agency of participants within the community, the diaspora experience and discussions of identity. This project takes a decolonial theoretical framework and is centred on developing a collective memory — “collective, plural, yet individual” (Nora, 1989), questioning traditional structures of historical representation within virtual reality.
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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 | 0.003 |
| Science and technology studies | 0.015 | 0.011 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".