Support Requirements for Cognitive Readiness in Complex Operations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The authors report two experiments studying the requirements for effective decision making in a complex environment. The focus lies on three components of individual cognitive readiness: situation awareness (SA), problem solving, and decision making. Participants performed a simulated society management task in which they could allocate resources to stabilize a national crisis involving multiple interrelated factors (political, economic, environmental, and social). A striking aspect of this simulation is that even though information about the causes and effects within the system is available, most individuals fail to bring the system to the targeted state because of unintended consequences of their decisions. The experiments test the impact of two cognitive support tools designed to improve anticipation of future outcomes. Results show that supporting short-term anticipation (with perfectly accurate projections) was insufficient to improve effectiveness, but supporting long-term anticipation (with approximate projections) successfully improved performance in this complex environment. We conclude with a review of requirements that training and technological support should address to augment individual cognitive readiness for operations in complex environments and propose an extension to SA theory by conceptualizing a Level 4 SA (long-term projection) that may be particularly important to overcome the “wall of complexity.”
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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 it