Bibliographic record
Abstract
In The Arte of English Poesie, Puttenham defines “prosopopoeia” as a rhetorical term that attributes “any humane quality, as reason or speech to dombe creatures or other insensible things.” Spenser exploits this trope by providing foxes, apes, and a Blatant Beast with biting tongues that can speak what a man may not. But he also applies this trope on a larger scale; mankind, Spenser (following Ovid) laments, lives in an Iron Age, an age full of “wicked maladie,” a “stonie one” (Prosopopoia or Mother Hubberd’s Tale 8; Faerie Queene V.Proem.2). Here, Spenser ascribes an insensible thing, an “age,” with ethical and moral—but in- and non-human—characteristics. In this “age,” men of “flesh and bone” risk being “degendered,” “transformed into hardest stone” (V.Proem.2). What, we might ask, can Iron or stone say to us (or about us) that otherwise might remain mute? This paper quarries Spenser’s “degendering” of Iron and man, human and stone, to put pressure on the distinction between what Jane Bennett terms “dull” and “vibrant” categories of matter. Spenser’s prosopopoeia, I argue, presents us with an indistinct vision of the human and invites reflection on what it means to inhabit a world both indifferent and intimately continuous with us.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".