Multicommunicating in Meetings: Effects of Locus, Topic Relatedness, and Meeting Medium
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
While meetings are a frequently used management tool, they also tend to be costly and less effective than desired. Multicommunication in meetings (Meeting MC)—being simultaneously engaged both in an organizational meeting and in one or more technology-mediated secondary conversations—has become increasingly prevalent and can affect meeting outcomes. Based on Goffman’s dramaturgical lens, media synchronicity, and compartmentalization, the present study examines how the outcomes of engaging in Meeting MC are affected by three key factors: Locus (the location of the people with whom one engages in a second conversation), Meeting Medium (the technology used to conduct a meeting), and Topic Relatedness (whether the topics being discussed in a meeting are related to the second conversation). Analyses of survey data suggest that how these three factors and their interactions affect meetings when Meeting MC occurs vary depending on whether a meeting is face-to-face (FTF) or technology-mediated.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it