Zoom and Beyond: New Frontiers and Evidence on Virtual Communication and Multicultural Teams
Bibliographic record
Abstract
This symposium examines the dynamic landscape of multicultural virtual teams in the post-COVID-19 era, advocating for a re-examination of research on virtual communication in multicultural teams. Established findings, rooted in the contrast between text-based and face-to-face communication, may not generalize to the new normal in which digital communication tools like Zoom, Microsoft Teams Slack, or Basecamp offer media-rich communication channels that make nonverbal behaviors and cultural differences in these behaviors much more salient. Accordingly, the key question that guides this symposium is: How can multicultural virtual teams thrive in a world where technological advances enable rich verbal and nonverbal communication among team members? To answer this question, we bring together four evidence-based papers that explore new frontiers in virtual communication and multicultural teams. Two of the papers explore a new cultural dimension of high/low-context communication and associated nonverbal behaviors in the context of virtual teams and two papers examine team processes and outcomes in global virtual teams. Collectively, the papers provide timely insights into various aspects of nonverbal communication, as well as the social, cultural, cognitive, and metacognitive skills required in media-rich digital and culturally diverse environments. In doing so, this symposium offers a comprehensive understanding of the challenges and opportunities faced by virtual teams, aiming to pave the way for improved teamwork in the future. Non-verbal Communication and Virtuality, Relational Processes, and Team Performance Author: Valerie Alexandra; San Diego State U. Author: Nancy Buchan; Darla Moore School of Business, U. of South Carolina Author: Wendi Lyn Adair; U. of Waterloo Author: Ruonan ZHAO; Xi'an Jiaotong U. Author: Ye Zhang; Tesla ‘Silent language’ in intercultural communication Author: Thomas Rockstuhl; Nanyang Technological U. Author: Kok Yee Ng; Nanyang Technological U. Author: Soon Ang; Nanyang Technological U. Expected vs Observed Challenges of Communication in GVTs: Effects on Interactions and Performance Author: Thomas Rockstuhl; Nanyang Technological U. Joint Effects of Cultural and Virtual Skills on Task Coordination in Virtual Multicultural Teams Author: Ella Glikson; Graduate School of Business Administration Bar Ilan U. Author: Shelly Lev-Koren; Technion - Israel Institute of Technology Author: Miriam Erez; Technion - Israel Institute of Technology How Global Virtual Teams Cultivate Intercultural Communication Competence? A Constructivist Approach Author: Fernando Trochez; Georgia State U. Author: Leigh Anne Liu; Georgia State U.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".