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Record W7033975324

The Strange Case of Mrs. Darling's Kiss: Why Peter and Wendy Needs a New Icelandic Translation

2018· dissertation· en· W7033975324 on OpenAlexaboutno aff

Bibliographic record

VenueSkemman · 2018
Typedissertation
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsCircumstantial evidenceSubject (documents)GloomPretextDemotionParaphernalia
DOInot available

Abstract

fetched live from OpenAlex

This essay explores the history behind the story and the character of Peter Pan, who was created by the Scottish author J. M. Barrie at the beginning of the 20th century, and how they continue to entertain readers and audiences today. It demonstrates how the character of Peter Pan was formed in the mind of the author long before the story was published, due to his older brother’s death at thirteen, and his acquaintance with a family of five young boys. It further addresses how the story was not written as a children’s story originally, as the character first appeared in a short story collection for adults, and how the novel Peter and Wendy is meant to entertain children and adults alike. The existence of the story of Peter Pan in Icelandic literature is then considered through different translations and the implications of the fact that there is only one Icelandic translation in existence which presents the novel as a whole, and not as a shortened, simplified children’s book, adapted to suit very young readers through illustrations rather than text. Lastly, a translation by Sigríður Thorlacius from 1947 is examined, demonstrating how the language is antiquated, and the narration abridged in such a manner that it fails to address the adult reader, which results in my conclusion that the novel is in need of a new Icelandic translation. The essay’s appendix includes my translation of the novel’s first chapter.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.877
Threshold uncertainty score0.535

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.022
GPT teacher head0.310
Teacher spread0.288 · 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 designOther design
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

Citations0
Published2018
Admission routes1
Has abstractyes

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