Some pragmatic functions of conversational facial gestures1
Bibliographic record
Abstract
Abstract Conversational facial gestures are not emotional expressions ( Ekman, 1997 ). Facial gestures are co-speech gestures – configurations of the face, eyes, and/or head that are synchronized with words and other co-speech gestures. Facial gestures are the most frequent facial actions in dialogue, and the majority serve pragmatic (meta-communicative) rather than referential functions. A qualitative microanalysis of a close-call story illustrates three pragmatic facial gestures in their macro- and micro-context: (a) The narrator’s thinking faces ( Goodwin & Goodwin, 1986 ) occurred as the narrator was getting started, and they accompanied verbal collateral signals of delay, such as “uh” or “um”. (b) The narrator pointed at his hand gestures with his head and eyes ( Streeck, 1993 ), drawing the addressee’s attention to depictions that would later be crucial to the close call. (c) The meta-communicative functions of smiles included marking the narrator’s description of danger as ironic or humorous, hinting at key elements, and acknowledging errors.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".