The Implication of DMIP on the Translation of Deliberate Metaphors in The Last Quarter of the Moon
Bibliographic record
Abstract
Our paper argues that DMIP is not only a method for identifying potentially deliberate metaphors but also a process of deconstructing a metaphor by tracing back its mapping relations. We employ DMIP to identify the deliberate metaphors in the translation process of The Last Quarter of the Moon and compare the identification results to evaluate the changes in the meaning reconstruction of deliberate metaphors in the English target text. We find that the meaning construction and discourse function of deliberate metaphor in the target text is strengthened or weakened due to the increase or decrease of metaphorical expressions. To maintain the equivalent meaning of deliberate metaphor in the target text, the deliberate nature, the number and content of metaphorical expressions, and the conceptual mappings should be kept unchanged. Omitting any of these elements may alter the meaning construction of deliberate metaphor and thus undermine its communicative function in literary translation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".