Renormalization theory and wargaming: multi-layered wargames
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
Generally speaking, wargames are tools for exploring human decision-making in an environment with incomplete and imperfect information. They can provide important insights into the complexity of military operations or can be used to generate novel ideas. However, if an analyst desired to conduct analyses spanning multiple warfare levels, the only feasible approach would be to select the largest domain and the highest resolution to accommodate even the smallest scales involved. This paper develops a theoretical framework based on the renormalization theory for a multi-layered approach to wargaming. This approach would enable representing variety of warfare scales within a single wargame, while avoiding the overhead that would have arisen from trying to represent desired scenarios at the highest required temporary and spatial scales. The proposal of a conceptual framework for multi-scale wargaming is demonstrated on a simplest possible example of hybrid wargames used in support of NATO concept development.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 it