Conversational styles and personality characteristics in women's close friendships and acquaintance relationships.
Bibliographic record
Abstract
Fourteen women engaged in two separate conversations (one with a close friend and one with an acquaintance) and discussed two topics with different task demands (shared similarities magnified by discussing memories the conversational partners share; differences magnified by discussing revealed differences of opinions between conversational partners). Audio taped conversations were coded for conversational turn-taking behaviors such as overlaps, simultaneous speech and successful interruptions. Speakers used a conversational style that included more overlaps and simultaneous speech when conversational partners' shared similarities were magnified than when conversational partners' differences were magnified. Additionally, compared to the women partners in the conversations with the acquaintances, the conversational style between women partners in the close friend conversations was more similar in terms of fast-paced turn-taking (i.e., overlaps). There was no relationship found between conversational behaviorsand personality characteristics (i.e., extraversion).
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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) | 0.003 | 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 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".