The Author's Three Bodies: Codicological Intentionalism and the Medieval Text
Bibliographic record
Abstract
This article takes issue with medievalists’ curated textual practices that coalesce on codicological intentionalism, that is, the implied position of (re)constructing authorial intention through the study of manuscripts and handwriting. Rather than criticize this practice, the article challenges medievalists to come clean about what they are doing, to acknowledge their methodological vantage point and, thus, to admit to investments in the project of intentionalism. Authorial intention is discussed as a function of the text/context debate; the tripartite division of authorship is analyzed in premodern settings; how codicological intentionalism operates is explained; and, finally, this phenomenon is shown to have parallels in a cognate discourse that has been ignored by literary medievalists, namely, the study of the Synoptic Gospels. Codicological intentionalism balances materialist with historicist certainties and probabilities; it offers a viable methodology for reconciling textual with authorial objectives.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.033 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".