Incentivizing Good Governance Beyond Regulatory Minimums: The Civil Nuclear Sector
Notice bibliographique
Résumé
The consequences from a blended cyber‐physical terrorist attack on a nuclear power plant are potentially catastrophic. Sabotage of the plant or theft and subsequent use of radiological materials can potentially lead to blackouts, deaths, and injuries and even a release of radiological materials. This threat continues to evolve in sophistication and complexity and is outpacing the ability and resources of governments to anticipate risks and to protect their critical infrastructure and the public from harm. Policymakers are working to keep up with the rapid onset of these threats to reinforce the resilience of critical infrastructure. Cyber vulnerabilities including insider threats are also evolving, with cyberattacks on nuclear facilities the tip of the iceberg as more sophisticated advanced persistent threats develop. This paper suggests governments look beyond regulations and policy directives to harness the power and energy of the market to incentivize operators to voluntarily adopt security measures beyond regulatory requirements. Good organizational governance is important and necessary to secure critical infrastructure including nuclear facilities and increasingly can be rewarded by the market. The definition of what is good organizational governance matters to investors, lenders, insurers, regulators, and the public. Is the organization going to be able to function effectively as an enterprise and provide a return to investors, pay back its loans, protect its workers and community, including the environment? In the nuclear field, the stakes can be high—with stakeholders depending on a stable baseload electric supply without safety or security incidents, especially of a radiological nature. This article documents findings from a multi‐year project to identify incentives for nuclear security beyond regulatory minimums, with a focus on nuclear power plants. We assessed the importance of standards and developed a “Good Governance Template” to support owners/managers in obtaining benefits and reducing potential liabilities. We found that market incentives are developing in areas such as insurance, credit, and other rating systems to support the development of good governance, including incentives for companies to demonstrate due care in the management of risks, especially cyber risks. Building a business case for nuclear security based on these incentives is an important step forward in securing our nuclear future, especially in terms of cyber risks.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».