A Study on the Principles and Strategies of Brand Translation From a Perspective of Functional Equivalence
Bibliographic record
Abstract
With economic globalization, trades all over the world have become more frequent, commodities have circulated more rapidly, and diversified consumer demands have been also met. The public has come to realize the importance of brand effect in stimulating consumption and exploring market. The promotion of advertisement on the product is beyond the reach of other forms and has been favored by the public. With the continuous emergence of foreign products, advertisements tend to have more diversified forms and plentiful connotations. In this context, it’s especially important to study on the principles and strategies in foreign brand translation. From a perspective of functional equivalence, this article proposes the “Three Aesthetics” principle and association principle in brand translation, has an introduction to the commonly used translation methods, and puts forward examples to further discuss the feasibility to implement foreign brand translation under the guidance of functional equivalence.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".