MétaCan
Menu
Back to cohort
Record W2044971204 · doi:10.5539/jsd.v8n4p187

Some Questions of Linguocultural Specificity Communication at the English Humour Translation

2015· article· en· W2044971204 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Sustainable Development · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicLanguage, Communication, and Linguistic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLinguisticsLiterary translationTarget textTranslation studiesExpression (computer science)PsychologySource textSociologyComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

This problem is relevant today because it is necessary to study the issues of the correlation of language, culture and translation, so far as translation is a link between linguistic cultures speakers. Obvious lack of researches in the field of linguocultural specificity affects the quality of the translation and the adequacy of reflection of ethno-linguistic worldview in the minds of other languages speakers. The objective of the article is to identify the degrees of interaction of language and culture in the translation process to provide a deep penetration in the national associated meanings of original literary works. Leading approach to the study of this problem is the analysis that was carried out on basis of descriptive, comparative methods, on the method of a literary text description, involving elements of linguistic and cultural analysis. Methodological basis became researches in linguistics, intercultural communication and translation studies. The paper revealed that linguocultural humour study suggests the priority coverage of the values that are relevant for the compared cultures. These values may get different expression in humorous texts. English humour includes relevant characteristics of universal humour and humour of those social groups that make up the English nation. The article materials may be useful for further research in this area, for effective translation techniques development.

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.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.534
Threshold uncertainty score0.701

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.047
GPT teacher head0.318
Teacher spread0.271 · 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