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Record W4318539256 · doi:10.1093/res/hgad008

<scp>Ema Vyroubalová</scp> and <scp>James Robert Wood</scp> (eds). <i>The Literary Papers of the Reverend Jermyn Pratt (1723–1791)</i>

2023· article· en· W4318539256 on OpenAlexaff
Philip Trotter

Bibliographic record

VenueThe Review of English Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMulticultural Socio-Legal Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPoetrySisterComedyArt historyArtPoliticsHistoryLiteratureClassicsSociologyLawAnthropology

Abstract

fetched live from OpenAlex

It is often assumed that some of the people remembered by Christopher Smart in the last fragment of Jubilate Agno (1758–1763) visited him during his detention in Potter’s madhouse. Jermyn Pratt, Norfolk clergyman and Smart’s fellow student at Cambridge, might not have been among Smart’s visitors, but the ‘mad’ poet interceded for Pratt’s father and family nevertheless: ‘Let Ruston, house of Ruston rejoice with Fulviana Herba, ab inventore, good to provoke urine. Lord have mercy upon Roger Pratt and his family.’ Other references to Pratt, his sister Harriot (Smart’s former love), and their Norfolk home, Ryston Hall, feature in Smart’s writings. Pratt’s place in literary history has rested on his association with Smart until now. This noteworthy and enterprising volume, carefully prepared and annotated by Ema Vyroubalová and James Robert Wood, brings Pratt’s dramatic, poetic, and essayistic works into print, establishing him as ‘an imaginative and idiosyncratic writer in his own right’ (2). From the uproarious comedy The Grange (c. 1774) to the sobering tract A Modest Address to Lewis (c. 1784), Pratt’s literary papers provide fresh and lively insights into the culture, society, and politics of provincial Norfolk in the eighteenth century.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: Review · Consensus signal: Review
Teacher disagreement score0.052
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0080.005
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0520.039

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 head0.027
GPT teacher head0.308
Teacher spread0.281 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations0
Published2023
Admission routes1
Has abstractyes

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