MétaCan
Menu
Back to cohort
Record W4387607951 · doi:10.1080/14781700.2023.2261943

Translation and architecturally odd invented languages in science fiction

2023· article· en· W4387607951 on OpenAlexaff
Brian Mossop

Bibliographic record

VenueTranslation Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicLanguage and cultural evolution
Canadian institutionsYork University
Fundersnot available
KeywordsLinguisticsComputer scienceSyntaxGrammarHAMLET (protein complex)Representation (politics)LexiconLiteratureArtificial intelligencePhilosophyArt

Abstract

fetched live from OpenAlex

Almost all invented languages in science fiction have the same architecture as spoken human natural languages. The article discusses six exceptions: languages which appear to be unusable because of the way they handle figures of speech; speech or writing directly connected to thought; speech that is not linear; writing that is not linear and not a representation of speech; lexicon, syntax and writing but no speech; and impoverished languages. If these odd invented languages existed outside fiction, they would be untranslatable into a human natural language in much the same sense that pictures, or communications to us by non-human animals on Earth, are describable but interlingually untranslatable. The translations provided by science fiction authors to enable their plots to advance are better seen as intersemiotic renderings. The article concludes with some similarities between translation studies and science fiction studies and the benefits of considering architecturally odd languages.

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)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.047
Scholarly communication0.0070.007
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.112
GPT teacher head0.406
Teacher spread0.294 · 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 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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueTranslation StudiesSame topicLanguage and cultural evolutionFrench-language works237,207