A social cybernetic analysis of simulation-based, remotely delivered medical skills training in an austere environment: Developing a test bed for spaceflight medicine
Bibliographic record
Abstract
This paper describes analysis of medical skills training exercises that were conducted at an arctic research station. These were conducted as part of an ongoing effort to establish high fidelity medical simulation test bed capabilities in remote and extreme "space analogue" environments for the purpose studying medical care in spaceflight. The methodological orientation followed by the authors is that of "second order cybernetics," or the science of studying human systems where the observer is involved within the system in question. Analyses presented include the identification of three distinct phases of the training activity, and two distinct levels of work groups-- termed "first-order teams" and "second-order teams." Depending on the phase of activity, first-order and second-order teams are identified, each having it own unique structure, composition, communications, goals, and challenges. Several specific teams are highlighted as case examples. Limitations of this approach are discussed, as are potential benefits to ongoing and planned research activity in this area.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".