Bibliographic record
Abstract
Canada’s first mosque, the Al Rashid mosque in Edmonton, was built in 1938. In the years since, as Canada’s Muslim population has grown, close to two hundred mosques, Islamic centres, prayer spaces, and jamatkhanas have been built across the country. Beyond the Divide explores the mosques of Canada in their diversity, beauty, practicality, and versatility. From east to west and to the north, Tammy Gaber visits ninety mosques in more than fifty cities, including Canada’s most northern places of worship in Nunavut and the Northwest Territories. For nearly a century Muslims have made mosques in a variety of spaces, from converted shops and vacated churches to large, purpose-built complexes. Drawing on site photographs, architectural drawings, and interviews, Gaber explores the extraordinary diversity in how these spaces have been designed, built, and used – as places not only of worship, but of community gathering, education, charitable work, and civic engagement. Throughout, Beyond the Divide provides a groundbreaking analysis of gendered space in Canadian mosques, how these spaces are designed and reinforced, and how these divides shape community experience. The first comprehensive study of mosque history and architecture in Canada, Beyond the Divide reveals the mosque to be a dynamic building type that adapts to its context, from its climate and physical environment to the community it serves. Above all, mosque designs depend on the people who gather in them, and what those people strive for their mosques to be.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.031 | 0.022 |
| Scholarly communication | 0.017 | 0.010 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.052 | 0.007 |
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".