Bibliographic record
Abstract
Acknowledgements Introduction: Religions and the Making of Canada Jamie S. Scott, York University 1. Aboriginals Jordan Paper, University of Victoria 2. Catholic Christians Terence J. Fay, University of Toronto 3. Protestant Christians C.T. McIntire, University of Toronto 4. Jews Ira Robinson, Concordia University 5. Muslims Amir Hussain, Loyola Marymount University and Jamie S. Scott, York University 6. Hindus Paul Younger, McMaster University 7. Buddhists Jamie S. Scott, York University and Henry C.H. Shiu, University of Toronto 8. Sikhs Pashaura Singh, University of California, Riverside 9. Baha'is Will C. van den Hoonaard, University of New Brunswick and St. Thomas University Afterword: New Religious Movements and the Religions of Canadians Going Forward Jamie S. Scott, York University, with contributions from Irving Hexham and Karla Poewe, University of Calgary Appendix a: 2001 Census Tables: Selected Religions Appendix b: 2001 Census Tables: Selected Religions by Immigrant Status and Immigration Period Contributors Index
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.002 |
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".