The Interaction of Metaphor and Metonymy in the Chinese Expressions of Body-part terms Yan and Mu L'INTERACTION ENTRE LA METAPHORE ET LA METONYMIE DANS LES EXPRESSIONS CHINOISES SUR LES PARTIES DU CORPS—YAN ET MU EN VERSION CHINOISE (OEIL)
Bibliographic record
Abstract
This is a study of metaphoric and metonymic expressions containing body-part terms yan and mu in Chinese to investigate the interaction of the metaphor and metonymy. While recognizing their differences from cognitive perspective, with metaphor involving things from two different domains and metonymy involving things within the same domain, I suggest that they also have similarities in certain respects. Based on the analysis of the self-made and small-scale corpus of Chinese texts of the metaphor and metonymy related to yan and mu, the author finds that metaphor and metonymy do not occur in isolation in Chinese. Key words: metaphor, metonymy, differences, similarities, interaction Resume: C’est une etude sur les expressions metaphoriques et metonymiques de la langue chinoise dans lesquelles les termes de yan et de mu sont utilises en vue d’examiner l’interaction entre la metaphore et la metonymie. Bien que les differences entre ces deux figures de rhetorique soient reconnues sous l’angle cognitif, c’est-a-dire que la metaphore implique des choses de deux domaines differents, alors que la metonymie implique des choses du meme domaine, il nous suggere qu’il existe aussi des similitudes entre ces deux figures. Base sur l’analyse d’un corpus concernant l’emploi de ces deux figures, qui est originaire des documents chinois authentiques et est fait par l’auteur elle-meme, l’auteur s’apercoit qu’ etant mises en utilisation, la metaphore et la metonymie ne sont pas sans rapport entre eux dans la langue chinoise. Mots-Cles: metaphore, metonymie, difference, similitude, interaction
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".