Are All Lockdown Teams Created Equally? Work Characteristics and Team Perceived Virtuality
Bibliographic record
Abstract
Team virtuality has been mostly conceptualized as structural features, such as the percentage of time team members communicate via technology. However, the perception of distance and of information deficits (team perceived virtuality, TPV) may be an indispensable construct to understand virtual teams’ functioning. The lockdowns imposed on most countries due to COVID-19 created virtual teams with high degrees of structural virtuality. With structural virtuality held constant among teams, we explore configurations of work characteristics (autonomy, interdependence, and organizational support) that influence TPV. With a sample of 296 multinational workers, a Latent Profile Analysis identified four distinct profiles of those work characteristics. Those profiles related differently to TPV. Contrary to previous findings, interdependence seems to play an important role in these teams high in structural virtuality when their autonomy is also high, highlighting the pivotal role of frequent interaction among team members, under conditions of high structural virtuality.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".