Bibliographic record
Abstract
Canada’s metaphor for integrating immigrants is the mosaic —vividly colored pieces of ethnicity, culture, racial identity, and language planted side by side, and in contrast to the melting pot of the American states, Canada is a nation of immigrants from all parts of the world, including the Arab world. The Arab community’s presence in Canada has not been investigated, represented, or responded to as thoroughly as other notable immigrant communities. This thesis begins with a literature review that underscores the fact that there is no one cohesive “Arab” identity, contrary to popular belief. Hence, moving forward with a focus on El Mashreq countries, this thesis investigates the heritage and social dynamics at the heart of El Mashreq culture, supported by a series of stories collected by the author to provide a humanist perspective towards the usually misconceived Arab community in Canada. Employing grafting—the binding of two separate plant pieces into one—as the research’s primary discourse and method of approach, the following thesis speculates on graft architecture as an advocacy tool for racialized minorities, specifically El Mashreq Arabs in Canada. Following the Being an Arab in Canada Study, carried out with the community in Canada with the goal of documenting authentic insight into their needs, a design proposal for an Ahwé—Arabic for coffeeshop—in Old Montreal is presented as a design solution that responds to the community’s longing for social interaction. The design is based on an exploration of contact zones—where disparate cultures meet—through a conscientious analysis of the French-inspired architecture of Cairo, Beirut, and Montreal, envisioning a unique graft of the three. This thesis ultimately argues that grafting can be utilized as an ever-evolving model for the weaving together of distinct cultures sharing space, when intricately implemented into all stages of architectural design; from program, to material use, and modern detailing.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.039 | 0.004 |
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".