Globalization, Multiculturalism and the Evolution of Suburban Toronto, Richmond Hill Iranian Community
Bibliographic record
Abstract
Canadian cities and their built form will continue to evolve as they are affected, by trends in globalization and its consequent mobilization of populations in mass immigration. This thesis investigates the impact on the buildings of the suburban areas that immigrant communities move to, and proposes to develop design strategies to establish a common built identity for communities shared by Canadians and new immigrants seeking a life in Canada. \nThis Architecture will deal with the impact of mass migration of North American Suburb and the creation of the ethnic enclaves. In particular, how the Iranian immigrant community can manifest their traditional building formats in the new urban context of the Toronto suburb of Richmond Hill. \nThe research is based on the study of the joint form and functions of typical buildings, both in Iranian traditional cities and the suburbs of Toronto. The concern of the design case studies is to develop a new interpretation building form and function, which answers to the needs of Iranian-Canadian citizens of Richmond Hill. Each interpretation is based on a transformation of a Canadian suburban building type using the forms, uses, and culturally defined habits found in the traditional Iranian architecture. \nThis thesis is looking at hybridized architecture, which combines the original architecture of home culture and standardized commercial and residential architecture of North American suburb. This study presents a house project as a private realm and represents a public realm; a café, and shopping plaza.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.008 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 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".