Order and Emotion: The Rhetoric of Disgust in Peter the Venerable's Adversus Iudaeos
Bibliographic record
Abstract
This thesis examines the definition of religious orthodoxy promulgated byPeter the Venerable in the Adversus Iudaeos, a twelfth-century anti-Judaic polemic.Scholars have thus far categorized this polemic as a typical and traditional guidebook designed to aid monks in the refutation of Jews using scripture, logical argumentation, and an engagement with post-biblical Jewish holy text (and in this case, the Talmud).Despite this categorization, scholars have neglected to discuss the role of emotions in categorizing Judaism.I argue that Peter uses the emotional rhetoric of disgust to alter the traditional polemical purpose ascribed to it.When Peter compares Jews to "useless vomit", he suggests that a Jewish way of thinking is filthy and worthy of disgust.These acts allow Peter the ability to unify and define his own version of Christian thought, and contrast it with the framework of thinking adopted by his rival monastic group, the Cistercians.There is probably no possible way I could every repay all the amazing people that made this thesis what it is today.Some four years ago, I was a simple teachers college graduate with only a fool's dream to come and make my mark on graduate level learning.Yet here I stand today with thesis in hand and a much deeper appreciation for the all those that supported me and pushed me to never settle for anything less than my best.This thesis is dedicated to my family, who always loved me unconditionally and instilled in me the value of education.This past year was fraught with change and yet Mom, Dad, and Stephen were constantly there to help out in any way they could.Thank you.This thesis is dedicated to Marc Saurette, who went above and beyond the role of a supervisor on countless occasions.The amount of interruptions and headaches I caused this man are staggering, yet Marc was always patient and supportive with me and he often knew just what to say.It was an honor and a privilege to be his student, and I would like to say that I did him proud.This thesis is also dedicated to my friends, both old and new.They made me feel like family, and stepped up when I needed them most.For all those sofa talks and office banter that lasted way longer than it should have, I thank you.To that end, this section would like to thank in particular Nick Courchesne, Thomas Marlatt, Mike Novacaska Rob Blades, Brad Wiebe, Adam Lake, and Emily Cuggy.aswell as the entire 2016 graduating class.These people truly made my masters degree memorable.I would also like to dedicate this thesis to Mélanie Bédard, because she never stopped believing in me.Regardless of what happens, I know that I am fortunate to have her as a supporter.And finally, I would like to dedicate this thesis to Joan White and all the faculty members that made my academic journey so memorable.Their tireless work in order to improve the student experience is nothing short of exceptional, and I believe that I am leaving Carleton in the best possible hands going forward.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".