Bibliographic record
Abstract
Objectives/research questions: Brand names not only serve to identify specific products and services, but also to convey information. Such information may depend on the sound of the word—independent of its semantic meaning. In this research, we propose that plosive consonants such as [b], [d], [p], and [t] (vs. fricative consonants such as [f], [l], [s], and [s]) elicit the feeling of doing something because of the articulatory movements their pronunciation requires. Method/ approach We ran three experimental studies in a behavioral lab with samples composed of French-speaking participants. Results Study 1 relies on implicit measures to demonstrate that plosive consonants are unconsciously associated with the semantic concept of action. Studies 2 and 3 put this property to the test in the context of threats to personal control. If plosive consonants can simulate action, threats to personal control should increase the perceived attractiveness of brand names that include such sounds since threats to personal control have been shown to trigger a willingness to act. Managerial/societal implications: Our results suggest that managers can project action based on the sounds of their brands—independently of their semantic meaning. Originality The demonstration of the capacity of plosive consonants to evoke action relies on the use of implicit measures and the replication of the observed effect across several studies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.913 | 0.877 |
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; the direct Gemma label and the distilled Codex classifier 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".