Failure and nerve in the academic study of religion : essays in honor of Donald Wiebe
Bibliographic record
Abstract
Preface 1. The Nerve of Donald Wiebe Luther H. Martin, University of Vermont 2. The Failure of Nerve in the Academic Study of Religion Donald Wiebe, Trinity College, University of Toronto General Failures 3. Catching Up with Marx: Truth, Myth, and the Niceties of Belief Matthew Day, Florida State University 4. Fixed Geomorphologies and the Shifting Sands of Time Darlene Juschka, University of Regina 5. A Critical History of Religion as a Psychological Phenomenon Janet Klippenstein, University of Alberta 6. Everything Old is New Again Russell T. McCutcheon 7. Revisiting the Confessional: Donald Wiebe's Small 'c' Confessional, Its Historical Entailments and Linguistic Entanglements Johannes C. Wolfart, Carleton University Special Failures 8. Failures (of Nerve?) in the Study of Islamic Origins Herbert Berg, University of North Carolina at Wilmington 9. The Failure of Islamic Studies Post-9/11: A Contextualization and Analysis Aaron W. Hughes, State University of New York at Buffalo 10. Religious Studies that Really Schmecks: Introducing Food to the Academic Study of Religion Michel Desjardins, Wilfrid Laurier University 11. Cultural Anthropology and Corinthian Food Fights: Structure and History in the Lord's Dinner John W. Parrish, Brown University 12. The Identity of Q in the First Century: Reproducing a Theological Narrative Sarah E. Rollens, University of Toronto 13. The Failure of Nerve to Recognize Violence in Early Christianity: The Case of the Parable of the Assassin Thomas Nicholas Schonhoffer, University of Toronto 14. Redescribing Iconoclasm: Holey Frescoes and Identity Formation Vaia Touna, University of Alberta In Lieu of Conclusion 15. The Irony of Religion William Arnal and Willi Braun
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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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.013 | 0.026 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".