Bibliographic record
Abstract
The paper explores the teaching of juvenilia in the context of an ongoing crisis in the humanities, arguing the need to introduce university students to the study of child writing by including it when studying non-juvenile texts, as distinct from staging a separate course on it. It offers examples of teaching John Ruskin’s juvenilia with his mature work but also with romanticism more generally. Ruskin’s early poetry can be read as evasive, the young writer cutting himself off from examining his feelings as they emerge in the writing process, especially as he documents what might be very personal topics such as his interactions with his parents and his developing maturation. The paper argues that students reading Ruskin’s juvenilia will have insights into The King of the Golden River, a mature work, and the masculinities it represents because it too refuses to pursue difficult themes. In a similar way, his juvenilia can be used in the undergraduate classroom to enhance understandings of romanticism in that the evasiveness in Ruskin’s poetry can be read as the consequence of Ruskin’s reading of the romantics and especially the image of the romantic child as developed in Wordsworth’s verse. Though the paper is on pedagogy and juvenilia, most of it consists of an analysis of Ruskin’s early verse.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.471 | 0.273 |
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".