Bibliographic record
Abstract
An enlightening evening of personal stories and reflections shared by Canadian Muslim women. This dialogue will reveal the diversity of the writers featured in this anthology and highlight varying perspectives that exist in the Muslim Diaspora.\n\nThe conversation will be moderated by Ray Hsu. Seemi Ghazi, lecturer in Classical Arabic at UBC, Poet, performer of Sufi vocal arts, and reciter of Quran, will grace the evening with poetic recitations that will open and close the evening with powerful messages.\n\nABOUT THE BOOK\nThese twenty-one personal stories are told by women from practically all backgrounds and persuasions—devout and not-so devout, professionals and housewives, westernized and traditional, wearing jeans, hijab, or niqab, straight and gay, and originally from Africa, North America, South Asia, the Middle East, and East Asia—revealing in their own ways what it means to them to be a Muslim woman (a "Muslimah"). What we get is a complex of stories, all challenging conventions and stereotypes, and united by two ideas—Islam (or the Quran) and nationality (Canadian).
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 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".