Multicommunicating During Team Meetings and Team Performance: An Experiment of Multi-level Effects
Bibliographic record
Abstract
With the rise of communication technologies, multicommunicating (MC), simultaneously engaging in multiple communication tasks via digital channels, has become increasingly common in workplaces. However, existing research largely focuses on individual-level factors influencing MC behavior and related outcomes. Extending this literature, we examine MC during team meetings (Meeting MC) - being simultaneously engaged both in an organizational meeting and in one or more technology-mediated secondary conversation(s) - and its effects on individual and team outcomes. Drawing upon the multilevel theorization of MC, we hypothesize that engaging in Meeting MC impacts not only the focal individual (MCer) but also team processes and performance. Using a between-subjects laboratory experiment, we tested these hypotheses with data from 37 teams (18 control and 19 manipulation teams). The results indicate that MCers experience higher levels of MC intensity and greater process losses compared to their teammates. Furthermore, teams exposed to Meeting MC experience lower team flow and transactive memory systems, and their performance is lower compared to teams with no meeting MC. We further discuss the implications of our research. Finally, we outline study limitations and propose directions for future research to explore the multilevel impacts of Meeting MC.
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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 | 0.001 | 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 | 0.001 |
| 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 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".