Public Placemaking and Diasporic Identities: Political Activism, Cultural Preservation, and Creating a Home among Tibetans in Toronto
Bibliographic record
Abstract
This thesis explores processes of public placemaking among Tibetans in Toronto. The Tibetan community in Toronto has arrived there fairly recently, about 20 years ago in the late 1990s. In this time, the community has established an ethnic enclave known as ‘Little Tibet’, and a Tibetan Canadian Cultural Centre. In this thesis, public placemaking in public space, the ethnic enclave ‘Little Tibet’ in the Parkdale neighbourhood, and in the Tibetan Canadian Cultural Centre are explored. The findings are based on five months of ethnographic research among the Tibetan community in Toronto, Canada. Methods comprised of semi-structured qualitative interviewing, a focus group, informal conversing, and participant observation. This study shows that through processes of public placemaking in public space, Little Tibet, and the cultural centre, the Tibetan community in Toronto strives towards their goals of drawing attention to human rights issues in Tibet, preserving Tibetan cultural traditions and values, and creating a home in Canada. Moreover, in these processes of public placemaking and in striving towards these three goals, Tibetans manifest different (combinations of) identities such as Tibetan, Tibetan-Canadian, and Indian, Nepali or Bhutanese. These identities are telling of the history of migration of this group of Tibetans. This thesis concludes that through processes of public placemaking, the Tibetan community in Toronto strives towards their goals and manifests their cultural identity.
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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 | 0.030 | 0.014 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".