The Multi-Faceted Nature of Virtual Teams
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
Despite their growing popularity in organizations, our understanding of virtual teams is still at an embryonic stage. As of today, the term “virtual team” has been loosely defined in the academic press, and empirical findings have been generalized across all types of virtual teams. Based on an extensive review of the literature and a series of in-depth interviews with more than 40 experienced virtual team members and leaders, we identified the key characteristics of virtual teamwork as well as those characteristics that distinguish among various virtual team configurations. We posit that researchers must now adopt a multidimensional view of virtual teams in order to adequately compare empirical findings, build a cumulative tradition in this field of research, and provide practitioners with a framework to help them manage virtual teams effectively. Researchers and practitioners must not only recognize the diversity of possible virtual team arrangements but also identify strategies and draw lessons that are contingent upon particular virtual team configurations.
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.
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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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