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Record W3030510188 · doi:10.29173/pathfinder13

Stories Re-Told

2020· article· en· W3030510188 on OpenAlexaffvenue
Anna Borynec

Bibliographic record

VenuePathfinder A Canadian Journal for Information Science Students and Early Career Professionals · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicShakespeare, Adaptation, and Literary Criticism
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAdaptation (eye)FolkloreDisciplineVariety (cybernetics)ScholarshipSet (abstract data type)VocabularyPerspective (graphical)Translation studiesConsilienceField (mathematics)Computer scienceEpistemologySociologyLinguisticsSocial scienceLiteraturePsychologyArtArtificial intelligenceAnthropology

Abstract

fetched live from OpenAlex

This paper introduces three umbrella terms (Literal Adaptation, Spirit Adaptation, and Creative Adaptation) that define the broad approaches to creating an adaptation through the consideration of the literature of six different fields and their approaches to the study of adaptation. They are as follows: the study of Classical Mythology (a sub-set of Classics), Cultural Studies, Adaptation Theory (from Film Studies), Fan Fiction Studies (from Fan Studies), Folklore Studies, and Translation Studies. While Library and Information Studies (LIS) does occasionally deal with adaptation, often in the form of Children's Literature and/or Fairy Tales, there is no widely-accepted theory or method to doing so. Therefore it is absent from the six disciplines that were reviewed, though it has substantial cross-over with each. As scholarship becomes more interdisciplinary, juggling the terms of a variety of fields becomes more important and more challenging. This paper aims to provide three accessible terms for those interested in studying adaptions from a broad or cross-disciplinary perspective that can substitute for the lengthy and specialized vocabulary of each individual discipline. It may also provide an example for others looking to similarly synthesize a set of cross-disciplinary vocabularies.

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 categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.791
Threshold uncertainty score0.998

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 studies0.0030.000
Scholarly communication0.0030.006
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 head0.109
GPT teacher head0.329
Teacher spread0.220 · 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 designQualitative
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
Published2020
Admission routes2
Has abstractyes

Explore more

Same venuePathfinder A Canadian Journal for Information Science Students and Early Career ProfessionalsSame topicShakespeare, Adaptation, and Literary CriticismFrench-language works237,207