Asset Management Through the Lens of Complex System Governance
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
This paper examines the applicability of Complex System Governance to advance Asset Management. Asset management (AM) is increasing in importance as more societal serving systems are becoming dependent on the value of assets and their management. However, AM as a discipline lacks coherent grounding in systems theory --- a means for understanding the structure, behavior, and performance of complex systems. Complex System Governance (CSG) is focused on the design, execution, and evolution of system functions that provide for communications, control, coordination, and integration of complex systems, including assets. CSG focuses on the structure and order of complex systems through a rigorous grounding in systems theory (the axioms and propositions that govern the structure, behavior, and performance of complex systems), management cybernetics (the science of organizational structure), and system governance (focused on the provision of direction, oversight, and accountability). In this paper, the intersection of AM and CSG is explored concerning the value that can accrue to both fields through their intersection and joint development. The opportunities that lie at the intersection of these fields are examined. This paper concludes the exploration with a discussion of the implications for moving forward in bringing the value offered by CSG to the governance of assets.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.003 |
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