Vocal Speed and Processing of Persuasive Messages: Curvilinear Processing Effects
Bibliographic record
Abstract
Abstract Most work on indicators of vocal confidence (and social influence work more broadly) examines linear relationships between variables. However, in some domains curvilinear (i.e., accelerating or decelerating) relationships may provide greater clarity in understanding human speech patterns. We review mixed past work on vocal speed as a case study, wherein faster vocal speed has been shown both to bolster and inhibit persuasion (e.g., by impairing processing). Across six total studies (N total = 3,958), we show that faster speed initially increases perceived source confidence and message processing but eventually the increase attenuates or reverses. Correspondingly, vocal speed has a decelerating relationship to participants’ processing of persuasive messages, as revealed by two main processes: argument quality effects on attitudes, and the correspondence between thought valence and attitudes. The present work highlights the potential value of high-powered examinations of curvilinear relationships in non-verbal phenomenon for which speed is likely to play a role.
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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 | 0.004 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".