Notice bibliographique
Résumé
ABSTRACT Historically, many response exercises conducted by the United States Coast Guard and other oil spill response stakeholders have been conducted as functional or full-scale exercises. With the increased demands placed on many U.S. agencies as a result of the terrorist attacks of September 11’ 2001, there is a greater need than ever to ensure that time spent in training and exercises produces positive and tangible results for the participants. In preparation for the joint US/Canadian response exercise, CANUSLANT 2002, the U.S. and Canadian Coast Guards decided to take a step back and look at the lessons learned from previous exercises. Based on this review, the Joint Response Team (JRT) decided to focus CANUSLANT 2002 as a training opportunity and to work on the lessons learned that were repeatedly identified in earlier CANUSLANT exercises. Perhaps the most common exercise conducted in oil spill response is the functional “command post” exercise where exercise participants are assigned to ICS (Incident Command System) staff elements. Participants then respond to an exercise scenario and prescripted injects that are provided to drive participant actions. With personnel turnover, transfers, and increased operational demands, many exercise participants struggle through the crisis phase of an incident scenario and never have the opportunity to learn what it is they are supposed to be doing. When all is said and done, many exercise participants are often simply go home happy that the exercise is over and done with. The goal for CANUSLANT 2002 was to produce an exercise where the participants accomplished something tangible; that long pending issues would be discussed and perhaps even resolved. The Exercise Design Team hoped that the participants walked away from the exercise saying that it was time well spent and not simply thankful that the exercise was over. This paper outlines the factors that led to the success of the CANUSLANT 2002 cross border response exercise. This paper also highlights some of the fundamentals for varying your approach to exercises to achieve tangible results while providing personnel the skills and training required to respond in the event of a real disaster.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
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 | 0,001 | 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 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,013 | 0,001 |
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».