Designing Serious Games for Senior Executive Strategic Decision Making
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
Senior executive strategic decision making is a prized skill. The analysis of available literature yields three key conclusions: i) strategic decision-making skills, especially in high complexity and ambiguity leverage ‘adaptive expertise' which is very different from the dominant discourse on narrow domain ‘expert performance;' ii) unlike focused skills which can be developed by concentrated, high repetition practice, adaptive expertise requires higher order meta-cognitive skills in addition to wide domain knowledge and managerial skills. Third, emerging literature suggests serious games can help to improve capabilities in decision making and cognitive skill, but there is a limited range of games or research explicitly focused on strategic decisions, while there is extensive body of knowledge on such simulations and measures for in-the-moment type decisions. The authors propose several frameworks and design requirements incorporating three levels of skills including higher cognition.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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 it