A. C. SPEARING, Textual Subjectivity: The Encoding of Subjectivity in Medieval Narratives and Lyrics.
Bibliographic record
Abstract
SPEARING's lucid and sagacious book is a response to prevalent assumptions about the ways subjectivity inheres in medieval lyrics and narratives. The book challenges the predominant expectation that analyses of such literature must proceed from an understanding of a personalized narrator. This book, in contrast, examines how subjectivity is inscribed in such texts as a textual phenomenon. Spearing's intention is not to offer a catholic theory, nor a comprehensive history, of textual subjectivity, but to critique habitual assumptions which subtend scholarly engagements of medieval literary subjectivities. As Spearing admits in his introductory chapter, he is often speaking to a scholarly vacuum, since theorists who do critique the assumption that literary texts are extensions of a human consciousness have largely ignored medieval literature (e.g. Stanzel, Theory of Narrative, or Cohn, Transparent Minds), while medievalists, though increasingly receptive to theory, have for the most part uncritically accepted narrator theories of medieval texts posited nearly a century ago by critics like George Kittredge. Certainly this vacuum invites scholarly attention, but it also means that Spearing is able to direct his criticism not at the theories of medievalists, but at their practices. This sometimes lends his criticism an air of eclectic opportunism: replete with refutation, but light on assertion. Even so, these practices certainly call for refutation, and this discussion does clear the ground for much future scholarship, making plain as it does that we did not necessarily know what we thought we knew.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.005 | 0.018 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.007 |
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".