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Colouratives in the English-Language Literary Text: Correlation of Direct and Indirect Meanings

2022· article· en· W4313204454 on OpenAlexaboutno aff
Alesya A. Gorzhaya

Bibliographic record

VenueCurrent Issues in Philology and Pedagogical Linguistics · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDiscourse Analysis and Cultural Communication
Canadian institutionsnot available
Fundersnot available
KeywordsMeaning (existential)MetonymyMetaphorLinguisticsLiteratureDystopiaWhite (mutation)ArtPhilosophyEpistemologyChemistry

Abstract

fetched live from OpenAlex

The article is devoted to the study of the correlation of direct and indirect meanings of colouratives that are used in the English-language literary text based on the material of women’s prose, in particular, the novel “The Handmaid’s Tale” (1985) by M. Atwood. As part of the analysis of theoretical and methodological material, it has been revealed that colouratives in a literary text contribute to the fact that the author of a literary text can implicitly convey to the reader a much larger amount of information: such words can evoke certain associations in the recipient, allow the author to attract his attention, create a visual, pictorial artistic reality that differs in one or another set of colours. During the analysis of the selected contexts (more than 500 fragments) with colouratives (516 units) from the literary work – a dystopian novel by Canadian writer Margaret Atwood “The Handmaid’s Tale”, a number of features have been identified. In the analyzed literary work, various colours have been used – ten frequently occurring and five less common ones. As part of the work with empirical material, the frequently occurring colouratives that do not have a transfer of meaning and less frequently used secondary colouratives with a transfer of meaning (metaphor and metonymy) have been identified. Some of the colour designations have had only a direct meaning. The colouratives white, red and black are very frequently used (almost a third of them has a semantic transfer). The colouratives blue (half of them has a transfer of semantics), pink (the fourth part is metaphorical or metonymic), green and gray (half of them with a transfer of semantics) and brown (one fifth has a semantic transfer) are quite often used. Besides, the author highlights the colouratives gold(en) (with a predominance of metaphors and metonymies) and silver (half of them with a transfer of semantics), which often denote not only the colour, but also the material from which this or that object is made. The least represented are the colouratives purple, yellow, orange, peach and ivory, which are completely or almost completely not characterized by any semantic transfers. In terms of structure, one-component colouratives prevail in relation to most colours and in both groups of colouratives, however, two-component structures are also quite frequent in case of direct nomination. The indirect meaning assumes various syntactic and morphological-syntactic models of the formation of colouratives (word composition, word composition + suffixation), including figurative comparisons with the elements as and like. As a result of the study of direct and figurative meanings of colouratives in M. Atwood’s novel «The Handmaid’s Tale» we come to the conclusion about the diversity of colouratives in terms of semantic transfers (metaphor, metonymy, metaphtonymy), structure and derivational models (from simple, single-component colouratives to complex multicomponent formations).

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)0.005
metaresearch head score (Gemma)0.040
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.040
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.005
Science and technology studies0.0020.009
Scholarly communication0.0060.007
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.433
Teacher spread0.324 · 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".

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Citations1
Published2022
Admission routes1
Has abstractyes

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