Societal Impacts of Infrastructure Failure Interdependencies: Building an Empirical Knowledge Base
Bibliographic record
Abstract
This paper discusses recent efforts to gather and synthesize empirical data on the societal impacts of infrastructure failure interdependencies (IFIs). A systematic database has been developed on IFIs and their social, economic, health, safety, and environmental consequences. Data pertain to several events, including the August 14, 2003 blackout (affecting the northeastern U.S. and eastern Canada), the 1998 Quebec ice storm, and three 2004 Florida hurricanes. The database emphasizes IFIs deriving from electric power disruptions. Data are drawn primarily from print/text media reports. Verification exercises are conducted against various other primary and secondary information sources. The database is used to comparatively assess patterns in the severity of societal consequences from IFIs, including characterizing hazard, infrastructure sectors, and impact types according to their "intensive" or "extensive" nature. Hurricanes and ice storms are found to be more similar to each other than to blackouts. Infrastructure sectors of greatest concern include transportation and utilities. Specific IFIs are identified that frequently occur and cause significant societal impacts. These results provide a basis for considering priorities for risk mitigation.
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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 | 0.012 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.037 | 0.022 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.011 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".