Bibliographic record
Abstract
From its opening mix of deliberately incongruous images (“mossy glens,” “substances like boils,” and “glowworm winks”) to its deft use of Victorian and modern theories of the grotesque, to its innovative concluding gambit, Taylor LeMaire’s essay maps its own way through two exceptionally complex poems and the rich terrain of the aesthetics of the grotesque. The essay is notably original first of all in comparing two classic Victorian texts very seldom considered in conjunction, though they were published within five years of each other. Secondly, LeMaire focuses not on the ugliness, lapses, and incongruity conventionally associated with the grotesque, but on its “positive” functions in both Browning’s “‘Childe Roland’” and Rossetti’s “Goblin Market.” After a close and convincing analysis of strategically chosen textual details, combining consideration of poetic form with metaphoric and thematic content, LeMaire concludes with a surprising but apt shift from visual to sonic modes of the grotesque. She pairs the blast of the “slug-horn” that occurs at the end of Childe Roland’s quest when he reaches the “dark tower” with the animal-human goblin men’s seductive “cries” that ring enticingly in our ears in the opening of Rossetti’s poem. An exemplary essay. Whether one sound is ultimately more “positive” and beneficial than the other is left more open to question. As Browning’s Roland says of the mysterious appearance of the dark tower, “solve it, you!” –Dr. Marjorie Stone
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".