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Record W2810694387 · doi:10.29173/jjs127

Teaching "the young idea how to shoot"

2018· article· en· W2810694387 on OpenAlexaffvenue
Lorna J. Clark

Bibliographic record

VenueJournal of Juvenilia Studies · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicThemes in Literature Analysis
Canadian institutionsCarleton University
Fundersnot available
KeywordsAmateurSisterCraftPoetryLiteratureAuntArtPublishingGirlExpression (computer science)HistoryArt historyVisual artsSociologyPsychology

Abstract

fetched live from OpenAlex

"The Burney family stood at the centre of cultural life of eighteenth- and nineteenth-century England, and excelled in several forms of artistic expression, especially in writing. Among the manuscripts preserved in the family archive are some collections of juvenilia produced by the children of Charles Rousseau and Esther Burney, Frances Burney’s elder sister. These literary projects helped the young authors to build confidence in their writing, refine their craft, and find a voice. This paper examines two: the first is an early example of a family-produced magazine that is patterned after one of the first-ever periodicals aimed at children. The second collection is a series of anthologies containing poems, plays, and stories written by Sophia Elizabeth Burney and dedicated to her novelist aunt. The plays seem designed to be performed in amateur theatricals; the stories contain images of female suffering, sharp satire on social pretentions, and a raucous (even violent) sense of humour that evoke the novels of Frances Burney. The newly discovered manuscripts reflect an environment that evidently encouraged creative play, self-expression, and artistic production. The study of these juvenile works yield insight into the creative world of the Burneys and, more generally, into the world of the child reader and writer in late eighteenth-century England.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.455
Threshold uncertainty score0.567

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.034
GPT teacher head0.295
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2018
Admission routes2
Has abstractyes

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