Bibliographic record
Abstract
Montreal, December 2019 Dear Readers: The Council for Research on Religion (CREOR) is pleased to announce the first edition of its E-Journal, The Journal of the Council for Research on Religion. This first issue deals with the theme of “Religion and Violence,” a SSHRC funded colloquium that took place on April 17th - 20th, 2018. The colloquium was a collaboration between members of McGill and Concordia University, further details concerning the colloquium can be found on the following site: https://creorgraduate.wordpress.com/religion-and-violence-colloquium/CREOR is Montreal's first academic research council in the field of Religious Studies. The Council is an inter-disciplinary and inter-university entity drawing on the expertise and research interests present in the city of Montreal. It consists of members from the disciplines of Religious Studies and other disciplines within Arts, as well as from Education, Law and Medicine, and other disciplines, such as Management and Music. CREOR is based in Montreal and collaborates with researchers from Montreal based universities and colleges and from around the world. Editorial Team for the Religion and Violence Vol. 1Chief Editors: Dr. Gerbern S. Oegema Dr. André Gagné Graduate Student Editors: Amanda Rosini Elyse MacLeod David Anthony Basham
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.307 | 0.243 |
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".