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Record W2766433014

Pirates and Prosthetics: Manly Messages for Managing Limb Loss in Victorian and Edwardian Adventure Narratives

2018· book-chapter· en· W2766433014 on OpenAlexaboutno aff
Ryan Sweet

Bibliographic record

VenueWhite Rose Research Online (University of Leeds, The University of Sheffield, University of York) · 2018
Typebook-chapter
Languageen
FieldArts and Humanities
TopicShort Stories in Global Literature
Canadian institutionsnot available
Fundersnot available
KeywordsAdventureNarrativeHistoryArtVisual artsArt historyLiterature
DOInot available

Abstract

fetched live from OpenAlex

Many of us associate pirates with prosthetic body parts. From wooden legs to hook hands, prostheses have frequently appeared in imaginative representations of pirates, such as Captain Hook from J. M. Barrie's 1904 play Peter Pan, Captain Barbosa and Ragetti from the Pirates of the Caribbean (2003–11) film series, the badges of the sports teams the Cornish Pirates and Pittsburgh Pirates, and the products and branding of the Woodenhand Brewery in Truro, Cornwall. Yet this prevalent association has not always existed. Its literary history is, in fact, curious. What we might consider the great age of pirate stories (c. 1858–1904) exhibits relatively few prosthesis-using characters, aside, of course, from one obvious example: Captain Hook. What we do, however, see in the fiction from this period, and what we today unthinkingly assume are wooden leg users, are a number of pirates who persevere with their deplorable duties in spite of disability.\n\nThe second quotation above, from Robert Michael Ballantyne's 1883 novel The Madman and the Pirate, exposes a rare example of a fictional pirate from this period who does use wooden legs – though it should be noted that this character, Captain Rosco, only loses his legs and begins wearing prosthetic replacements after his piratical career has ended.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.785
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.006
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.239
Teacher spread0.208 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueWhite Rose Research Online (University of Leeds, The University of Sheffield, University of York)Same topicShort Stories in Global LiteratureFrench-language works237,207