What is this accent? Effects of accent and language in international advertising contexts
Bibliographic record
Abstract
Abstract While accent effects have been studied in Western advertising contexts, there are contradictory findings on accent effects, and the moderating role of country‐of‐origin (COO), in other contexts. Few studies extended such accent effects to non‐English‐speaking cultural settings, particularly in emerging countries. This article fills this knowledge gap by examining accent and language effects on consumers’ perceived effectiveness of a spokesperson in Chinese advertising contexts. We explore how Chinese consumers evaluate spokespersons with standard and non‐standard accents, whether these accents are associated with belongingness, sophistication, and modernity, and whether COO moderates such accent and language effects on the perceived effectiveness of spokespersons. Across three studies, the findings demonstrate that compared with a spokesperson with a non‐standard accent (i.e., English‐accented Mandarin), spokespersons with standard accents (i.e., standard Mandarin and standard English) are perceived to be more effective. Furthermore, Chinese consumers associate standard Mandarin with belongingness, and standard English with sophistication and modernity, whereas English‐accented Mandarin has the lowest degree of these associations among the three accents. Although the moderating effect of COO is observed in Study 3, standard English is preferred for both advertised domestic and foreign products.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".