Meeting with Media: Comparing Synchronous Media Sharing and Icebreaker Questions in Initial Interactions via Video Chat
Bibliographic record
Abstract
Video chat continues to play an increasing role in the personal and professional lives of many people. When meeting someone for the first time via video chat, traditional icebreakers such as discussion questions may be used to ease conversation and facilitate disclosure; however, icebreaker questions have been shown to be less effective at facilitating relationships for some people than others. In this paper, we propose synchronously sharing online media as a more flexible, robust, and effective method of facilitating initial interactions in video chat. Our comparative study of icebreaker questions and media sharing reveals that shared media supports a different style of conversation than icebreakers, but results in equal levels of self-disclosure and trust along with higher levels of warranting and relatedness. Further, while the effectiveness of icebreakers in building trust is lower for individuals low in agreeableness, media sharing results in similar trust formation at all levels of agreeableness. Synchronous media sharing is a promising way of leveraging the digital context of video chat to better support early stages of relationships.
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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 | 0.010 | 0.074 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".