Bibliographic record
Abstract
Since the publication of Lakoff and Johnson’s Metaphors We Live By (1980), conceptual metaphor theory (CMT) has dominated metaphor studies. While one of the central tenets of that monograph is that metaphors are primarily a phenomenon of thought, not of language, conceptual metaphors have until recently been studied almost exclusively via verbal expressions. Another limitation of the CMT paradigm is that it has tended to focus on deeply embedded metaphors rather than on creative metaphors of the kind that Black (1979) discusses. One result of this focus is that relatively little attention is paid in CMT to the form and appearance a metaphor can assume (cf. Lakoff and Turner 1989). Clearly, which channel(s) of information (language, visuals, sound, gestures, among others) are chosen to convey a metaphor is a central factor in how a metaphor is construed and interpreted. A healthy theory of metaphor as a structuring element of thought therefore requires systematic examination of both its multimodal and its creative manifestations. Conversely, research into non-verbal and multimodal metaphor can help the theorization of multimodality.In this paper it is shown that creative metaphors occurring in commercials usually draw on a combination of language, pictures, and non-verbal sound. After an inventory of parameters involved in the analysis of multimodal metaphors, ten cases are discussed, with specific attention to the role of the various modes in the metaphors’ construal and interpretation. On the basis of the case studies, the last sections of the paper discuss three issues that are crucial for further study: (1) the ways in which similarity is cued in multimodal, as opposed to verbal, metaphors; (2) the problems adhering to the verbalization of multimodal metaphors; (3) the influence of textual genre on the interpretation of multimodal metaphors.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".