Managing Current Complexity: Critical Energy Infrastructure Failures in North America
Bibliographic record
Abstract
This paper applies the competing theories of High Reliability Organizations (HRO) and Normal Accidents Theory (NAT), two competing views of risk management in highly-complex and tightly-coupled systems, in analyzing the 1998 Ice Storm and the 2003 Blackout to examine vulnerabilities in North America’s critical energy infrastructure (CEI). Inferences are then made by highlighting the similarities and differences in the two cases, which are then used to draw lessons for public managers regarding the protection of CEIs. As CEIs are highly-complex and tightly-coupled systems, failures stemming from complex and uncertain risks are inevitable. There is an increasingly low tolerance for failure in energy infrastructure because society’s critical infrastructures have become increasingly interdependent. Public managers must regulate CEIs in order to ensure an emphasis is placed on safety and security while also finding ways to reduce unnecessary complexities. It is through the adoption of such measures that public managers will aid in minimizing the cascading effects of inevitable failures.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".