The Effect of Nonlexical Verbal Signals on the Perceived Authenticity, Empathy and Understanding of a Listener
Bibliographic record
Abstract
Active listening plays an important role in the relationship between clients and therapists. Here, we investigated whether variations of the confirmatory nonlexical verbal communication signal “mmh” influenced perceived authenticity, empathy, and understanding of a listener. Eighty-one participants were in a conversation with an interviewer and reported about a difficult work experience. They were randomly assigned to one of three groups: the control group did not receive any verbal feedback from the interviewer; in one experimental group (1x-mmh), the interviewer uttered several monosyllabic confirmatory nonlexical verbal signals (“mmh”) during the presentation; in a second experimental group (3x-mmh) the interviewer voiced several tri-syllabic “mmh-mmh-mmh” while listening. All participants were then asked to rate the perceived authenticity, empathy, and understanding of the interviewer. Participants in the 3x-mmh condition rated the interviewer to be significantly less authentic than those in the other two groups. No differences in reported empathy and understanding were found. The use of consecutive confirmatory nonlexical verbal signals (“mmh”), at least as currently implemented, may influence the perceived authenticity of a listener.
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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 | 0.003 | 0.027 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".