Infrastructure and the Operational Art: A Handbook for Understanding, Visualizing, and Describing Infrastructure Systems
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 Army's understanding of infrastructure as an operational variable has been evolving over the past 30 years in response to significant events ranging from international conflicts to domestic weather-related disasters.These experiences have combined to drive a significant shift in infrastructure doctrine, which now demands that commanders and staffs understand, visualize, and describe the infrastructure variable to accomplish the Army's assigned infrastructure missions of protecting, restoring, and developing infrastructure-all missions essential to restoring stability after conflict or disaster.Current Army doctrine, however, does not say how commanders and staffs are to approach these challenging tasks.This report presents a cognitive framework for understanding, visualizing, and describing infrastructure by using five conceptual models created to allow commanders and staffs to think critically, creatively, and completely about infrastructure problems.The report also includes the scholarship behind the models including verification, validation, and certification as well as example applications of the models to actual situations.Infrastructure is a concern for both civil society and the military, and the models work equally well in both.The authors actively solicit feedback from any reader on the use, application, and improvement of these models.
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 | 0.000 | 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