Assessing Team Performance in Complex Team-Based Command and Control Missions Through Information Sharing and Team Cohesion
Bibliographic record
Abstract
In complex command and control (C2) scenarios, effective team performance depends on the development of shared situation awareness (SA) among team members with heterogeneous expertise. Civilians were assigned heterogeneous roles in ad hoc emergency management teams responding to a fictional hurricane scenario, such that mission success would require effective sharing of their unique knowledge during a team discussion session. Whereas previously published work using this dataset found relationships between SA and self-reported team cohesion, the current work compared team decisions against a benchmark “expert” team, where each expert received all information from all roles prior to the discussion session. Results showed that greater similarity between civilian and expert team decisions, indicating more effective information sharing, was related to higher team cohesion, more updating of individual SA, and greater overlap in shared SA. Facilitating information sharing and promoting team cohesion may be valuable methods for improving team effectiveness in C2 scenarios.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".