Getting with the times: a narrative review of the literature on group decision making in virtual environments and implications for promotions committees
Bibliographic record
Abstract
INTRODUCTION: Concerns around the time and administrative burden of trainee promotion processes have been reported, making virtual meetings an attractive option for promotions committees in undergraduate and postgraduate medicine. However, whether such meetings can uphold the integrity of decision-making processes has yet to be explored. This narrative review aimed to summarize the literature on decision making in virtual teams, discuss ways to improve the effectiveness of virtual teams, and explore their implications for practice. METHODS: In August 2017, the Web of Science platform was searched with the terms 'decision making' AND 'virtual teams' for articles published within the last 20 years. The search yielded 336 articles, which was narrowed down to a final set of 188 articles. A subset of these, subjectively deemed to be of high-quality and relevant to the work of promotions committees, was included in this review. RESULTS: Virtual team functioning was explored with respect to team composition and development, idea generation and selection, group memory, and communication. While virtual teams were found to potentially offer a number of key benefits over face-to-face meetings including convenience and scheduling flexibility, inclusion of members at remote sites, and enhanced idea generation and external storage, these benefits must be carefully weighed against potential challenges involving planning and coordination, integration of perspectives, and relational conflict among members, all of which can potentially reduce decision-making quality. DISCUSSION: Avenues to address these issues and maximize the outcomes of virtual promotions meetings are offered in light of the evidence.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".