Особливості генези та функціонування синестетичної метафори в оглядах українських страв та продуктів харчування (на матеріалі You Tube відео англійськомовних блогерів).
Bibliographic record
Abstract
The article is devoted to the analysis of the synaesthetic metaphor peculiarities, i. e. its genesis and functioning within the conversational English-speaking Internet discourse. The synaesthetic metaphor is viewed as a result of synaesthesia which on the level of perception influences the inventory of the language means involved by the speaker. The object of the present study is the synaesthetic metaphor which finds its expression in the English-speaking Internet discourse, the subject of the research is the peculiarities of the synaesthetic metaphor genesis and functioning. The source of the investigated empirical material are video reviews of Ukrainian dishes and food given by English-speaking American, British, and Canadian bloggers (overall duration of 7 hours 47 minutes 33 seconds) uploaded onto YouTube video-sharing platform. Application of the continuous sampling method, componential analysis, descriptive and quantitative methods allow to single out 37 samples (47 uses in speech) of the synaesthetic metaphor, outline patterns of synaesthetic transfers and determine their productivity. The most productive pattern of the synaesthetic transfers singled out is the model “look –> touch”, less productive are the model “taste –> touch”, “taste –> appearance”, and “sound –> touch”. The least productive patterns of the synaesthetic metaphoric transfers are “taste –> smell”, “smell –> taste”, “smell –> touch”, “touch –> look”, and “look –> taste”. Apart from this, as a result of the synaesthetic transfers directions analysis, the place of contact and distant receptors in the process of perceptual information transmission is determined, where the sensory area of the touch acts as the most frequent source of perceptual features transmission, while the areas of visual and taste perceptions function in most cases as sensory sensation recipients.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.044 | 0.013 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".