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Record W3123216347 · doi:10.1353/book.66806

Mythodologies: Methods in Medieval Studies, Chaucer, and Book History

2018· book· en· W3123216347 on OpenAlexaboutno aff
Gretchen van Slyke, Martine Reid

Bibliographic record

VenuePunctum Books · 2018
Typebook
Languageen
FieldArts and Humanities
TopicMedieval Literature and History
Canadian institutionsnot available
Fundersnot available
KeywordsMedieval historyHistoryArtClassics

Abstract

fetched live from OpenAlex

Mythodologies challenges the implied methodology in contemporary studies in the humanities. We claim, at times, that we gather facts or what we will call evidence, and from that form hypotheses and conclusions. Of course, we recognize that the sum total of evidence for any argument is beyond comprehension; therefore, we construct, and we claim, preliminary hypotheses, perhaps to organize the chaos of evidence, or perhaps simply to find it; we might then see (we claim) whether that evidence challenges our tentative hypotheses. Ideally, we could work this way. Yet the history of scholarship and our own practices suggest we do nothing of the kind. Rather, we work the way we teach our composition students to write: choose or construct a thesis, then invent the evidence to support it.This book has three parts, examining such methods and pseudo-methods of invention in medieval studies, bibliography, and editing. Part One, “Noster Chaucer,” looks at examples in Chaucer studies, such as the notion that Chaucer wrote iambic pentameter, and the definition of a canon in Chaucer. “Our” Chaucer has, it seems, little to do with Chaucer himself, and in constructing this entity, Chaucerians are engaged largely in self-validation of their own tradition. Part Two, “Bibliography and Book History,” consists of three studies in the field of bibliography: the recent rise in studies of annotations; the implications of presumably neutral terminology in editing, a case-study in cataloguing. Part Three, “Cacophonies: A Bibliographical Rondo,” is a series of brief studies extending these critiques to other areas in the humanities. It seems not to matter what we talk about: meter, book history, the sex life of bonobos. In all of these discussions, we see the persistence of error, the intractability of uncritical assumptions, and the dominance of authority over evidence.TABLE OF CONTENTS //Part I. Noster ChaucerusChap. 1. How Many Chaucerians Does it Take to Count to Eleven? The Meter of Kynaston’s 1635 Translation of Troilus and Criseyde and its Implications for Chaucerian MetricsChap. 2. Chaucer’s “Rude Times”Chap. 3. Meditation on Our Chaucer and the History of the CanonCoda. Godwin’s Portrait of ChaucerPart II. Bibliography and Book HistoryChap. 4. The Singularities of Books and Reading .Chap. 5. Editorial ProjectingChap. 6. The Haunting of Suckling’s Fragmenta Aurea (1646)Coda. T. F. Dibdin: The Rhetoric of BibliophiliaPart III. Cacophonies: A Bibliographic RondoFakes and Frauds: The “Flewelling Antiphonary” and Galileo’s Sidereus NunciusModernity and Middle EnglishThe Quantification of ReadabilityThe Elephant Paper and Histories of Medieval DramaThe Pynson Chaucer(s) of 1526: Bibliographical CircularityMargaret Mead and the BonobosReading My LibraryABOUT THE AUTHORJoseph A. Dane is Professor of English at the University of Southern California. His books on book history and bibliography include Blind Impressions: Methods and Mythologies in Book History (Pennsylvania, 2013), Out of Sorts: On Typography and Print Culture (Pennsylvania, 2011), What is a Book? The Study of Early Printed Books (Notre Dame, 2012), and The Myth of Print Culture: Essays on Evidence, Textuality, and Bibliographical Method (Toronto, 2003).

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 imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.028
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0090.009
Science and technology studies0.0070.044
Scholarly communication0.0180.015
Open science0.0020.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.167
GPT teacher head0.335
Teacher spread0.168 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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