A Study on the Pragmatic Value of Interpersonal Metaphor in Literary Works — A Case Study of Tess of the D 'Urbervilles
Bibliographic record
Abstract
Grammatical metaphor refers to depicting the same scenes or things in the objective world with different forms of expression. It mainly includes two parts: interpersonal metaphor and ideational metaphor. Interpersonal metaphor is divided into metaphors of mood and metaphors of modality. Metaphors of mood are the transfer from one modal domain to another. The metaphors of modality change from implicit to explicit and reflect in the form of proposition. Language not only has the function of expressing the speaker's personal experience and inner activity, but also can express the speaker's identity, attitude, motivation and his/her inference, judgment and evaluation of things. Therefore, based on the frequency of the use of interpersonal metaphor, the reader can accurately grasp the information exchanged by the speakers. This paper applies interpersonal metaphor to analyze the discourses of the main characters in Tess of the D'Urbervilles by using declarative which is used as command as well as question; interrogative, which is used as command as well as statement, etc. in metaphors of mood and using the subjective explicit as well as objective explicit in metaphors of modality. Through the different expressions of the character discourse, speech function embodied in the discourse is interpreted to help the reader understand the theme of the text more easily, thereby revealing the pragmatic value of interpersonal metaphor in the analysis of literary works.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.015 | 0.012 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".