Conceptual metaphors shape consumer psychology
Bibliographic record
Abstract
Abstract Marketers routinely use metaphors to compare abstract concepts to concrete concepts in remote domains. For example, a tagline “Supercharge your day” compares energy to electricity. Such messages aim to change consumer attitudes and behavior, but what impact do they have? According to Conceptual Metaphor Theory, metaphors can shape thought by borrowing knowledge of a concrete concept to understand and relate to an abstraction, despite their superficial differences. Supporting this claim is growing evidence that exposure to metaphoric messages prompts recipients to construe the metaphor's abstraction in ways that are analogous to the salient concrete concept. This article presents a selective review of this literature, focusing on studies pertaining to product evaluation and consumption attitudes. Discussion looks across findings to identify questions for future research. Taken as a whole, this research illuminates how, when, and for whom metaphoric messages are persuasive, with theoretical and practical implications for marketing, design, and persuasion.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.048 | 0.023 |
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; both teacher heads agree on what is shown here.
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".