Metaphors in Wine-tasting Notes in English and Spanish
Bibliographic record
Abstract
espanolLa metafora conceptual, para la linguistica cognit iva, implica entender un dominio semantico en terminos de otro. A menudo se ha considerado que las asociaciones conceptuales son universales, unidireccionales y dependientes del uso. Sin embargo, el concepto de niversalidad es muy controvertido ya que enf renta dos conceptos, el de universalidad y el de cultura; es decir, diferentes culturas pueden transmitir la misma realidad usando diferentes recursos metaforicos. El objetivo de este articulo es comprobar el concepto de universalidad en el lenguaje metafo rico de fichas de cata escritas por expertos. Nuestra metodologia implica la identificacion de las metaforas de acuerdo con determinados terminos clave y su posterior analisis en terminos cualitativos y cuantitativos. Nuestros resultados demuestran que las diferencias entre las culturas implicadas no parecen afectar al uso metaforico en las fichas de cata EnglishConceptual metaphor in cognitive linguistics involves understanding one semantic domain in terms of the other. Conceptual associations between domains have been considered universal, unidirectional and usage - based. However, the concept of universality is rather controversial, si nce it contradicts that of culture: different cultures may convey the same reality by using different metaphorical sources. The purpose of this paper is to examine to what extent the concept of universality holds true for metaphors found in wine - tasting no tes written by wine experts. Our corpus - based methodology involves identifying metaphors linked to selected key terms and analyzing them both quantitatively and qualitatively. Our results show that the differences in English and Spanish cultures do not see m to affect the metaphorical use of language in wine - tasting note
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".