Team Cognition During a Simulated Close Air Support Exercise: Results from a New Behavioral Rating Instrument 1
Bibliographic record
Abstract
This chapter discusses efforts to capture team cognition processes during the Canadian portion of Exercise Northern Goshawk with a Behaviorally Anchored Rating Scale (BARS) we designed for the purpose. Having identified the phases of Close Air Support (CAS) where team behaviors would be most evident, it sets about developing anchors for the BARS based on the behavioral markers of team cognition breakdown proposed by K. A. Wilson et al. The team Hierarchical Task Analysis (HTA) identified the different members of the broad CAS team but only the Forward Air Controller (FAC) and Pilot branches were developed in detail. The exercise was designed as a CAS, Time Sensitive Targeting (TST), and Troops in Contact (TIC) training event involving participants and researchers at simulation sites in Canada, the US, and the UK. Poor transmission quality on the simulated radio channel also made it difficult for the players to understand each other.
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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 | 0.001 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".