Anxiety/Uncertainty Management and Communication Accommodation in Women’s Brief Dyadic Conversations With a Stranger: An Idiodynamic Approach
Bibliographic record
Abstract
This study uses a combination of anxiety/uncertainty management theory and communication accommodation theory perspective to examine differences in the ways women converse with men or with other women. The study uses an innovative approach, the idiodynamic method, to gather detailed data on a per-second timescale. Participants ( n = 24) were randomly assigned to one of the two types of dyads: female–female or male–female. They then engaged in a videotaped conversation lasting approximately 2 to 5 min. Immediately afterward, participants watched the video of their conversation in separate rooms, during which each provided continuous, dynamic ratings of their anxiety level, and that of their partner, throughout the conversation. Participants were interviewed about the reasons for changes in their ratings of both themselves and their conversational partner. Following a grounded theory approach to analysis, six themes emerged from the interviews: awareness of the camera and researchers, comparison of self and partners, self-judgment, worry about other’s judgment, disinterest, and reaction to miscommunication. The data show that communication accommodation was done differently in the female-only versus female–male pairs, which might reflect processes involving uncertainty, group identification, and continuously negotiated meaning. There is value in using methods that investigate communication processes in real time because doing so allows instances of proposed theoretical differences between genders to emerge in actual conversation between persons.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".